{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "aa45eba8",
   "metadata": {},
   "source": [
    "# 01 - Exploration des Données - Home Credit Default Risk\n",
    "\n",
    "Ce notebook présente une analyse exploratoire complète des données du projet Home Credit Default Risk.\n",
    "\n",
    "**Objectif** : Comprendre les données, identifier les patterns importants et préparer le terrain pour la modélisation.\n",
    "\n",
    "**Inspiré de** : [Will Koehrsen - Start Here: A Gentle Introduction](https://www.kaggle.com/code/willkoehrsen/start-here-a-gentle-introduction)\n",
    "\n",
    "## Plan du Notebook\n",
    "\n",
    "1. **Configuration et Chargement des Données**\n",
    "2. **Exploration Initiale**\n",
    "3. **Analyse de la Variable Cible**\n",
    "4. **Analyse des Valeurs Manquantes**\n",
    "5. **Analyse des Types de Variables**\n",
    "6. **Analyse des Corrélations**\n",
    "7. **Analyse de l'Âge**\n",
    "8. **Détection d'Anomalies**\n",
    "9. **Variables EXT_SOURCE**\n",
    "10. **Conclusions et Prochaines Étapes**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5aa440b0",
   "metadata": {},
   "source": [
    "## 1. Configuration et Imports\n",
    "\n",
    "Importation des bibliothèques nécessaires pour l'analyse exploratoire."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "275912a2-420b-4456-8fa0-b8857a22f0b9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "✓ Bibliothèques importées avec succès\n"
     ]
    }
   ],
   "source": [
    "# Manipulation de données\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "# Visualisation\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# Configuration système pour les imports\n",
    "import sys\n",
    "import os\n",
    "\n",
    "# Suppression des warnings pour une sortie plus propre\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "# Configuration de l'affichage pandas\n",
    "pd.set_option('display.max_columns', None)  # Affiche toutes les colonnes\n",
    "pd.set_option('display.max_rows', 100)      # Affiche jusqu'à 100 lignes\n",
    "\n",
    "# Configuration du style des graphiques\n",
    "plt.style.use('seaborn-v0_8-darkgrid')\n",
    "sns.set_palette(\"husl\")\n",
    "\n",
    "print(\"✓ Bibliothèques importées avec succès\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6301ba1",
   "metadata": {},
   "source": [
    "## 2. Chargement des Données\n",
    "\n",
    "Nous utilisons la fonction `load_raw_data()` pour charger tous les fichiers de données disponibles."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "97cc9f29",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Current working directory: /home/valentin/Env_Python/OC_P6/notebooks\n",
      "Chargement depuis : /home/valentin/Env_Python/OC_P6/data/raw\n",
      "✓ Chargement de application_train.csv\n",
      "✓ Chargement de application_test.csv\n",
      "✓ Chargement de bureau.csv\n",
      "✓ Chargement de bureau_balance.csv\n",
      "✓ Chargement de credit_card_balance.csv\n",
      "✓ Chargement de installments_payments.csv\n",
      "✓ Chargement de POS_CASH_balance.csv\n",
      "✓ Chargement de previous_application.csv\n",
      "✓ Données chargées :\n",
      "  - Ensemble d'entraînement : (307511, 122)\n",
      "  - Ensemble de test : (48744, 121)\n"
     ]
    }
   ],
   "source": [
    "# Debug: Check what the current working directory is\n",
    "print(f\"Current working directory: {os.getcwd()}\")\n",
    "\n",
    "# Configuration du chemin du projet\n",
    "from pathlib import Path\n",
    "\n",
    "# Trouve le dossier OC_P6 en remontant depuis le notebook\n",
    "notebook_dir = Path.cwd()\n",
    "oc_p6_dir = None\n",
    "\n",
    "for parent in [notebook_dir] + list(notebook_dir.parents):\n",
    "    if (parent / \"data\" / \"raw\" / \"application_train.csv\").exists():\n",
    "        oc_p6_dir = parent\n",
    "        break\n",
    "    if parent.name == \"OC_P6\":\n",
    "        oc_p6_dir = parent\n",
    "        break\n",
    "\n",
    "if oc_p6_dir is None:\n",
    "    # Fallback: on remonte un niveau depuis le répertoire courant\n",
    "    oc_p6_dir = notebook_dir.parent\n",
    "\n",
    "project_root = str(oc_p6_dir)\n",
    "sys.path.insert(0, project_root)\n",
    "\n",
    "# Reload the module to ensure BASE_DIR is recalculated\n",
    "import importlib\n",
    "if 'src.load_data' in sys.modules:\n",
    "    importlib.reload(sys.modules['src.load_data'])\n",
    "\n",
    "# Import de la fonction de chargement\n",
    "from src.load_data import load_raw_data\n",
    "\n",
    "# Chargement des données\n",
    "raw_data = load_raw_data()\n",
    "\n",
    "# Extraction des DataFrames principaux\n",
    "app_train = raw_data.application_train\n",
    "app_test = raw_data.application_test\n",
    "\n",
    "print(f\"✓ Données chargées :\")\n",
    "print(f\"  - Ensemble d'entraînement : {app_train.shape}\")\n",
    "print(f\"  - Ensemble de test : {app_test.shape}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f907e8b7",
   "metadata": {},
   "source": [
    "## 3. Exploration Initiale\n",
    "\n",
    "Examinons la structure de base des données d'entraînement."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "3f37c75e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=== Premières lignes du dataset ===\n"
     ]
    },
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SK_ID_CURR</th>\n",
       "      <th>TARGET</th>\n",
       "      <th>NAME_CONTRACT_TYPE</th>\n",
       "      <th>CODE_GENDER</th>\n",
       "      <th>FLAG_OWN_CAR</th>\n",
       "      <th>FLAG_OWN_REALTY</th>\n",
       "      <th>CNT_CHILDREN</th>\n",
       "      <th>AMT_INCOME_TOTAL</th>\n",
       "      <th>AMT_CREDIT</th>\n",
       "      <th>AMT_ANNUITY</th>\n",
       "      <th>AMT_GOODS_PRICE</th>\n",
       "      <th>NAME_TYPE_SUITE</th>\n",
       "      <th>NAME_INCOME_TYPE</th>\n",
       "      <th>NAME_EDUCATION_TYPE</th>\n",
       "      <th>NAME_FAMILY_STATUS</th>\n",
       "      <th>NAME_HOUSING_TYPE</th>\n",
       "      <th>REGION_POPULATION_RELATIVE</th>\n",
       "      <th>DAYS_BIRTH</th>\n",
       "      <th>DAYS_EMPLOYED</th>\n",
       "      <th>DAYS_REGISTRATION</th>\n",
       "      <th>DAYS_ID_PUBLISH</th>\n",
       "      <th>OWN_CAR_AGE</th>\n",
       "      <th>FLAG_MOBIL</th>\n",
       "      <th>FLAG_EMP_PHONE</th>\n",
       "      <th>FLAG_WORK_PHONE</th>\n",
       "      <th>FLAG_CONT_MOBILE</th>\n",
       "      <th>FLAG_PHONE</th>\n",
       "      <th>FLAG_EMAIL</th>\n",
       "      <th>OCCUPATION_TYPE</th>\n",
       "      <th>CNT_FAM_MEMBERS</th>\n",
       "      <th>REGION_RATING_CLIENT</th>\n",
       "      <th>REGION_RATING_CLIENT_W_CITY</th>\n",
       "      <th>WEEKDAY_APPR_PROCESS_START</th>\n",
       "      <th>HOUR_APPR_PROCESS_START</th>\n",
       "      <th>REG_REGION_NOT_LIVE_REGION</th>\n",
       "      <th>REG_REGION_NOT_WORK_REGION</th>\n",
       "      <th>LIVE_REGION_NOT_WORK_REGION</th>\n",
       "      <th>REG_CITY_NOT_LIVE_CITY</th>\n",
       "      <th>REG_CITY_NOT_WORK_CITY</th>\n",
       "      <th>LIVE_CITY_NOT_WORK_CITY</th>\n",
       "      <th>ORGANIZATION_TYPE</th>\n",
       "      <th>EXT_SOURCE_1</th>\n",
       "      <th>EXT_SOURCE_2</th>\n",
       "      <th>EXT_SOURCE_3</th>\n",
       "      <th>APARTMENTS_AVG</th>\n",
       "      <th>BASEMENTAREA_AVG</th>\n",
       "      <th>YEARS_BEGINEXPLUATATION_AVG</th>\n",
       "      <th>YEARS_BUILD_AVG</th>\n",
       "      <th>COMMONAREA_AVG</th>\n",
       "      <th>ELEVATORS_AVG</th>\n",
       "      <th>ENTRANCES_AVG</th>\n",
       "      <th>FLOORSMAX_AVG</th>\n",
       "      <th>FLOORSMIN_AVG</th>\n",
       "      <th>LANDAREA_AVG</th>\n",
       "      <th>LIVINGAPARTMENTS_AVG</th>\n",
       "      <th>LIVINGAREA_AVG</th>\n",
       "      <th>NONLIVINGAPARTMENTS_AVG</th>\n",
       "      <th>NONLIVINGAREA_AVG</th>\n",
       "      <th>APARTMENTS_MODE</th>\n",
       "      <th>BASEMENTAREA_MODE</th>\n",
       "      <th>YEARS_BEGINEXPLUATATION_MODE</th>\n",
       "      <th>YEARS_BUILD_MODE</th>\n",
       "      <th>COMMONAREA_MODE</th>\n",
       "      <th>ELEVATORS_MODE</th>\n",
       "      <th>ENTRANCES_MODE</th>\n",
       "      <th>FLOORSMAX_MODE</th>\n",
       "      <th>FLOORSMIN_MODE</th>\n",
       "      <th>LANDAREA_MODE</th>\n",
       "      <th>LIVINGAPARTMENTS_MODE</th>\n",
       "      <th>LIVINGAREA_MODE</th>\n",
       "      <th>NONLIVINGAPARTMENTS_MODE</th>\n",
       "      <th>NONLIVINGAREA_MODE</th>\n",
       "      <th>APARTMENTS_MEDI</th>\n",
       "      <th>BASEMENTAREA_MEDI</th>\n",
       "      <th>YEARS_BEGINEXPLUATATION_MEDI</th>\n",
       "      <th>YEARS_BUILD_MEDI</th>\n",
       "      <th>COMMONAREA_MEDI</th>\n",
       "      <th>ELEVATORS_MEDI</th>\n",
       "      <th>ENTRANCES_MEDI</th>\n",
       "      <th>FLOORSMAX_MEDI</th>\n",
       "      <th>FLOORSMIN_MEDI</th>\n",
       "      <th>LANDAREA_MEDI</th>\n",
       "      <th>LIVINGAPARTMENTS_MEDI</th>\n",
       "      <th>LIVINGAREA_MEDI</th>\n",
       "      <th>NONLIVINGAPARTMENTS_MEDI</th>\n",
       "      <th>NONLIVINGAREA_MEDI</th>\n",
       "      <th>FONDKAPREMONT_MODE</th>\n",
       "      <th>HOUSETYPE_MODE</th>\n",
       "      <th>TOTALAREA_MODE</th>\n",
       "      <th>WALLSMATERIAL_MODE</th>\n",
       "      <th>EMERGENCYSTATE_MODE</th>\n",
       "      <th>OBS_30_CNT_SOCIAL_CIRCLE</th>\n",
       "      <th>DEF_30_CNT_SOCIAL_CIRCLE</th>\n",
       "      <th>OBS_60_CNT_SOCIAL_CIRCLE</th>\n",
       "      <th>DEF_60_CNT_SOCIAL_CIRCLE</th>\n",
       "      <th>DAYS_LAST_PHONE_CHANGE</th>\n",
       "      <th>FLAG_DOCUMENT_2</th>\n",
       "      <th>FLAG_DOCUMENT_3</th>\n",
       "      <th>FLAG_DOCUMENT_4</th>\n",
       "      <th>FLAG_DOCUMENT_5</th>\n",
       "      <th>FLAG_DOCUMENT_6</th>\n",
       "      <th>FLAG_DOCUMENT_7</th>\n",
       "      <th>FLAG_DOCUMENT_8</th>\n",
       "      <th>FLAG_DOCUMENT_9</th>\n",
       "      <th>FLAG_DOCUMENT_10</th>\n",
       "      <th>FLAG_DOCUMENT_11</th>\n",
       "      <th>FLAG_DOCUMENT_12</th>\n",
       "      <th>FLAG_DOCUMENT_13</th>\n",
       "      <th>FLAG_DOCUMENT_14</th>\n",
       "      <th>FLAG_DOCUMENT_15</th>\n",
       "      <th>FLAG_DOCUMENT_16</th>\n",
       "      <th>FLAG_DOCUMENT_17</th>\n",
       "      <th>FLAG_DOCUMENT_18</th>\n",
       "      <th>FLAG_DOCUMENT_19</th>\n",
       "      <th>FLAG_DOCUMENT_20</th>\n",
       "      <th>FLAG_DOCUMENT_21</th>\n",
       "      <th>AMT_REQ_CREDIT_BUREAU_HOUR</th>\n",
       "      <th>AMT_REQ_CREDIT_BUREAU_DAY</th>\n",
       "      <th>AMT_REQ_CREDIT_BUREAU_WEEK</th>\n",
       "      <th>AMT_REQ_CREDIT_BUREAU_MON</th>\n",
       "      <th>AMT_REQ_CREDIT_BUREAU_QRT</th>\n",
       "      <th>AMT_REQ_CREDIT_BUREAU_YEAR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>100002</td>\n",
       "      <td>1</td>\n",
       "      <td>Cash loans</td>\n",
       "      <td>M</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>202500.0</td>\n",
       "      <td>406597.5</td>\n",
       "      <td>24700.5</td>\n",
       "      <td>351000.0</td>\n",
       "      <td>Unaccompanied</td>\n",
       "      <td>Working</td>\n",
       "      <td>Secondary / secondary special</td>\n",
       "      <td>Single / not married</td>\n",
       "      <td>House / apartment</td>\n",
       "      <td>0.018801</td>\n",
       "      <td>-9461</td>\n",
       "      <td>-637</td>\n",
       "      <td>-3648.0</td>\n",
       "      <td>-2120</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Laborers</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Business Entity Type 3</td>\n",
       "      <td>0.083037</td>\n",
       "      <td>0.262949</td>\n",
       "      <td>0.139376</td>\n",
       "      <td>0.0247</td>\n",
       "      <td>0.0369</td>\n",
       "      <td>0.9722</td>\n",
       "      <td>0.6192</td>\n",
       "      <td>0.0143</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0690</td>\n",
       "      <td>0.0833</td>\n",
       "      <td>0.1250</td>\n",
       "      <td>0.0369</td>\n",
       "      <td>0.0202</td>\n",
       "      <td>0.0190</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0252</td>\n",
       "      <td>0.0383</td>\n",
       "      <td>0.9722</td>\n",
       "      <td>0.6341</td>\n",
       "      <td>0.0144</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0690</td>\n",
       "      <td>0.0833</td>\n",
       "      <td>0.1250</td>\n",
       "      <td>0.0377</td>\n",
       "      <td>0.022</td>\n",
       "      <td>0.0198</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0250</td>\n",
       "      <td>0.0369</td>\n",
       "      <td>0.9722</td>\n",
       "      <td>0.6243</td>\n",
       "      <td>0.0144</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0690</td>\n",
       "      <td>0.0833</td>\n",
       "      <td>0.1250</td>\n",
       "      <td>0.0375</td>\n",
       "      <td>0.0205</td>\n",
       "      <td>0.0193</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>reg oper account</td>\n",
       "      <td>block of flats</td>\n",
       "      <td>0.0149</td>\n",
       "      <td>Stone, brick</td>\n",
       "      <td>No</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>-1134.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>100003</td>\n",
       "      <td>0</td>\n",
       "      <td>Cash loans</td>\n",
       "      <td>F</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "      <td>0</td>\n",
       "      <td>270000.0</td>\n",
       "      <td>1293502.5</td>\n",
       "      <td>35698.5</td>\n",
       "      <td>1129500.0</td>\n",
       "      <td>Family</td>\n",
       "      <td>State servant</td>\n",
       "      <td>Higher education</td>\n",
       "      <td>Married</td>\n",
       "      <td>House / apartment</td>\n",
       "      <td>0.003541</td>\n",
       "      <td>-16765</td>\n",
       "      <td>-1188</td>\n",
       "      <td>-1186.0</td>\n",
       "      <td>-291</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Core staff</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>MONDAY</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>School</td>\n",
       "      <td>0.311267</td>\n",
       "      <td>0.622246</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0959</td>\n",
       "      <td>0.0529</td>\n",
       "      <td>0.9851</td>\n",
       "      <td>0.7960</td>\n",
       "      <td>0.0605</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.0345</td>\n",
       "      <td>0.2917</td>\n",
       "      <td>0.3333</td>\n",
       "      <td>0.0130</td>\n",
       "      <td>0.0773</td>\n",
       "      <td>0.0549</td>\n",
       "      <td>0.0039</td>\n",
       "      <td>0.0098</td>\n",
       "      <td>0.0924</td>\n",
       "      <td>0.0538</td>\n",
       "      <td>0.9851</td>\n",
       "      <td>0.8040</td>\n",
       "      <td>0.0497</td>\n",
       "      <td>0.0806</td>\n",
       "      <td>0.0345</td>\n",
       "      <td>0.2917</td>\n",
       "      <td>0.3333</td>\n",
       "      <td>0.0128</td>\n",
       "      <td>0.079</td>\n",
       "      <td>0.0554</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0968</td>\n",
       "      <td>0.0529</td>\n",
       "      <td>0.9851</td>\n",
       "      <td>0.7987</td>\n",
       "      <td>0.0608</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.0345</td>\n",
       "      <td>0.2917</td>\n",
       "      <td>0.3333</td>\n",
       "      <td>0.0132</td>\n",
       "      <td>0.0787</td>\n",
       "      <td>0.0558</td>\n",
       "      <td>0.0039</td>\n",
       "      <td>0.01</td>\n",
       "      <td>reg oper account</td>\n",
       "      <td>block of flats</td>\n",
       "      <td>0.0714</td>\n",
       "      <td>Block</td>\n",
       "      <td>No</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-828.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>100004</td>\n",
       "      <td>0</td>\n",
       "      <td>Revolving loans</td>\n",
       "      <td>M</td>\n",
       "      <td>Y</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>67500.0</td>\n",
       "      <td>135000.0</td>\n",
       "      <td>6750.0</td>\n",
       "      <td>135000.0</td>\n",
       "      <td>Unaccompanied</td>\n",
       "      <td>Working</td>\n",
       "      <td>Secondary / secondary special</td>\n",
       "      <td>Single / not married</td>\n",
       "      <td>House / apartment</td>\n",
       "      <td>0.010032</td>\n",
       "      <td>-19046</td>\n",
       "      <td>-225</td>\n",
       "      <td>-4260.0</td>\n",
       "      <td>-2531</td>\n",
       "      <td>26.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Laborers</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>MONDAY</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Government</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.555912</td>\n",
       "      <td>0.729567</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-815.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>100006</td>\n",
       "      <td>0</td>\n",
       "      <td>Cash loans</td>\n",
       "      <td>F</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>135000.0</td>\n",
       "      <td>312682.5</td>\n",
       "      <td>29686.5</td>\n",
       "      <td>297000.0</td>\n",
       "      <td>Unaccompanied</td>\n",
       "      <td>Working</td>\n",
       "      <td>Secondary / secondary special</td>\n",
       "      <td>Civil marriage</td>\n",
       "      <td>House / apartment</td>\n",
       "      <td>0.008019</td>\n",
       "      <td>-19005</td>\n",
       "      <td>-3039</td>\n",
       "      <td>-9833.0</td>\n",
       "      <td>-2437</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Laborers</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>WEDNESDAY</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Business Entity Type 3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.650442</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-617.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>100007</td>\n",
       "      <td>0</td>\n",
       "      <td>Cash loans</td>\n",
       "      <td>M</td>\n",
       "      <td>N</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>121500.0</td>\n",
       "      <td>513000.0</td>\n",
       "      <td>21865.5</td>\n",
       "      <td>513000.0</td>\n",
       "      <td>Unaccompanied</td>\n",
       "      <td>Working</td>\n",
       "      <td>Secondary / secondary special</td>\n",
       "      <td>Single / not married</td>\n",
       "      <td>House / apartment</td>\n",
       "      <td>0.028663</td>\n",
       "      <td>-19932</td>\n",
       "      <td>-3038</td>\n",
       "      <td>-4311.0</td>\n",
       "      <td>-3458</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Core staff</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>THURSDAY</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Religion</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.322738</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1106.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   SK_ID_CURR  TARGET NAME_CONTRACT_TYPE CODE_GENDER FLAG_OWN_CAR  \\\n",
       "0      100002       1         Cash loans           M            N   \n",
       "1      100003       0         Cash loans           F            N   \n",
       "2      100004       0    Revolving loans           M            Y   \n",
       "3      100006       0         Cash loans           F            N   \n",
       "4      100007       0         Cash loans           M            N   \n",
       "\n",
       "  FLAG_OWN_REALTY  CNT_CHILDREN  AMT_INCOME_TOTAL  AMT_CREDIT  AMT_ANNUITY  \\\n",
       "0               Y             0          202500.0    406597.5      24700.5   \n",
       "1               N             0          270000.0   1293502.5      35698.5   \n",
       "2               Y             0           67500.0    135000.0       6750.0   \n",
       "3               Y             0          135000.0    312682.5      29686.5   \n",
       "4               Y             0          121500.0    513000.0      21865.5   \n",
       "\n",
       "   AMT_GOODS_PRICE NAME_TYPE_SUITE NAME_INCOME_TYPE  \\\n",
       "0         351000.0   Unaccompanied          Working   \n",
       "1        1129500.0          Family    State servant   \n",
       "2         135000.0   Unaccompanied          Working   \n",
       "3         297000.0   Unaccompanied          Working   \n",
       "4         513000.0   Unaccompanied          Working   \n",
       "\n",
       "             NAME_EDUCATION_TYPE    NAME_FAMILY_STATUS  NAME_HOUSING_TYPE  \\\n",
       "0  Secondary / secondary special  Single / not married  House / apartment   \n",
       "1               Higher education               Married  House / apartment   \n",
       "2  Secondary / secondary special  Single / not married  House / apartment   \n",
       "3  Secondary / secondary special        Civil marriage  House / apartment   \n",
       "4  Secondary / secondary special  Single / not married  House / apartment   \n",
       "\n",
       "   REGION_POPULATION_RELATIVE  DAYS_BIRTH  DAYS_EMPLOYED  DAYS_REGISTRATION  \\\n",
       "0                    0.018801       -9461           -637            -3648.0   \n",
       "1                    0.003541      -16765          -1188            -1186.0   \n",
       "2                    0.010032      -19046           -225            -4260.0   \n",
       "3                    0.008019      -19005          -3039            -9833.0   \n",
       "4                    0.028663      -19932          -3038            -4311.0   \n",
       "\n",
       "   DAYS_ID_PUBLISH  OWN_CAR_AGE  FLAG_MOBIL  FLAG_EMP_PHONE  FLAG_WORK_PHONE  \\\n",
       "0            -2120          NaN           1               1                0   \n",
       "1             -291          NaN           1               1                0   \n",
       "2            -2531         26.0           1               1                1   \n",
       "3            -2437          NaN           1               1                0   \n",
       "4            -3458          NaN           1               1                0   \n",
       "\n",
       "   FLAG_CONT_MOBILE  FLAG_PHONE  FLAG_EMAIL OCCUPATION_TYPE  CNT_FAM_MEMBERS  \\\n",
       "0                 1           1           0        Laborers              1.0   \n",
       "1                 1           1           0      Core staff              2.0   \n",
       "2                 1           1           0        Laborers              1.0   \n",
       "3                 1           0           0        Laborers              2.0   \n",
       "4                 1           0           0      Core staff              1.0   \n",
       "\n",
       "   REGION_RATING_CLIENT  REGION_RATING_CLIENT_W_CITY  \\\n",
       "0                     2                            2   \n",
       "1                     1                            1   \n",
       "2                     2                            2   \n",
       "3                     2                            2   \n",
       "4                     2                            2   \n",
       "\n",
       "  WEEKDAY_APPR_PROCESS_START  HOUR_APPR_PROCESS_START  \\\n",
       "0                  WEDNESDAY                       10   \n",
       "1                     MONDAY                       11   \n",
       "2                     MONDAY                        9   \n",
       "3                  WEDNESDAY                       17   \n",
       "4                   THURSDAY                       11   \n",
       "\n",
       "   REG_REGION_NOT_LIVE_REGION  REG_REGION_NOT_WORK_REGION  \\\n",
       "0                           0                           0   \n",
       "1                           0                           0   \n",
       "2                           0                           0   \n",
       "3                           0                           0   \n",
       "4                           0                           0   \n",
       "\n",
       "   LIVE_REGION_NOT_WORK_REGION  REG_CITY_NOT_LIVE_CITY  \\\n",
       "0                            0                       0   \n",
       "1                            0                       0   \n",
       "2                            0                       0   \n",
       "3                            0                       0   \n",
       "4                            0                       0   \n",
       "\n",
       "   REG_CITY_NOT_WORK_CITY  LIVE_CITY_NOT_WORK_CITY       ORGANIZATION_TYPE  \\\n",
       "0                       0                        0  Business Entity Type 3   \n",
       "1                       0                        0                  School   \n",
       "2                       0                        0              Government   \n",
       "3                       0                        0  Business Entity Type 3   \n",
       "4                       1                        1                Religion   \n",
       "\n",
       "   EXT_SOURCE_1  EXT_SOURCE_2  EXT_SOURCE_3  APARTMENTS_AVG  BASEMENTAREA_AVG  \\\n",
       "0      0.083037      0.262949      0.139376          0.0247            0.0369   \n",
       "1      0.311267      0.622246           NaN          0.0959            0.0529   \n",
       "2           NaN      0.555912      0.729567             NaN               NaN   \n",
       "3           NaN      0.650442           NaN             NaN               NaN   \n",
       "4           NaN      0.322738           NaN             NaN               NaN   \n",
       "\n",
       "   YEARS_BEGINEXPLUATATION_AVG  YEARS_BUILD_AVG  COMMONAREA_AVG  \\\n",
       "0                       0.9722           0.6192          0.0143   \n",
       "1                       0.9851           0.7960          0.0605   \n",
       "2                          NaN              NaN             NaN   \n",
       "3                          NaN              NaN             NaN   \n",
       "4                          NaN              NaN             NaN   \n",
       "\n",
       "   ELEVATORS_AVG  ENTRANCES_AVG  FLOORSMAX_AVG  FLOORSMIN_AVG  LANDAREA_AVG  \\\n",
       "0           0.00         0.0690         0.0833         0.1250        0.0369   \n",
       "1           0.08         0.0345         0.2917         0.3333        0.0130   \n",
       "2            NaN            NaN            NaN            NaN           NaN   \n",
       "3            NaN            NaN            NaN            NaN           NaN   \n",
       "4            NaN            NaN            NaN            NaN           NaN   \n",
       "\n",
       "   LIVINGAPARTMENTS_AVG  LIVINGAREA_AVG  NONLIVINGAPARTMENTS_AVG  \\\n",
       "0                0.0202          0.0190                   0.0000   \n",
       "1                0.0773          0.0549                   0.0039   \n",
       "2                   NaN             NaN                      NaN   \n",
       "3                   NaN             NaN                      NaN   \n",
       "4                   NaN             NaN                      NaN   \n",
       "\n",
       "   NONLIVINGAREA_AVG  APARTMENTS_MODE  BASEMENTAREA_MODE  \\\n",
       "0             0.0000           0.0252             0.0383   \n",
       "1             0.0098           0.0924             0.0538   \n",
       "2                NaN              NaN                NaN   \n",
       "3                NaN              NaN                NaN   \n",
       "4                NaN              NaN                NaN   \n",
       "\n",
       "   YEARS_BEGINEXPLUATATION_MODE  YEARS_BUILD_MODE  COMMONAREA_MODE  \\\n",
       "0                        0.9722            0.6341           0.0144   \n",
       "1                        0.9851            0.8040           0.0497   \n",
       "2                           NaN               NaN              NaN   \n",
       "3                           NaN               NaN              NaN   \n",
       "4                           NaN               NaN              NaN   \n",
       "\n",
       "   ELEVATORS_MODE  ENTRANCES_MODE  FLOORSMAX_MODE  FLOORSMIN_MODE  \\\n",
       "0          0.0000          0.0690          0.0833          0.1250   \n",
       "1          0.0806          0.0345          0.2917          0.3333   \n",
       "2             NaN             NaN             NaN             NaN   \n",
       "3             NaN             NaN             NaN             NaN   \n",
       "4             NaN             NaN             NaN             NaN   \n",
       "\n",
       "   LANDAREA_MODE  LIVINGAPARTMENTS_MODE  LIVINGAREA_MODE  \\\n",
       "0         0.0377                  0.022           0.0198   \n",
       "1         0.0128                  0.079           0.0554   \n",
       "2            NaN                    NaN              NaN   \n",
       "3            NaN                    NaN              NaN   \n",
       "4            NaN                    NaN              NaN   \n",
       "\n",
       "   NONLIVINGAPARTMENTS_MODE  NONLIVINGAREA_MODE  APARTMENTS_MEDI  \\\n",
       "0                       0.0                 0.0           0.0250   \n",
       "1                       0.0                 0.0           0.0968   \n",
       "2                       NaN                 NaN              NaN   \n",
       "3                       NaN                 NaN              NaN   \n",
       "4                       NaN                 NaN              NaN   \n",
       "\n",
       "   BASEMENTAREA_MEDI  YEARS_BEGINEXPLUATATION_MEDI  YEARS_BUILD_MEDI  \\\n",
       "0             0.0369                        0.9722            0.6243   \n",
       "1             0.0529                        0.9851            0.7987   \n",
       "2                NaN                           NaN               NaN   \n",
       "3                NaN                           NaN               NaN   \n",
       "4                NaN                           NaN               NaN   \n",
       "\n",
       "   COMMONAREA_MEDI  ELEVATORS_MEDI  ENTRANCES_MEDI  FLOORSMAX_MEDI  \\\n",
       "0           0.0144            0.00          0.0690          0.0833   \n",
       "1           0.0608            0.08          0.0345          0.2917   \n",
       "2              NaN             NaN             NaN             NaN   \n",
       "3              NaN             NaN             NaN             NaN   \n",
       "4              NaN             NaN             NaN             NaN   \n",
       "\n",
       "   FLOORSMIN_MEDI  LANDAREA_MEDI  LIVINGAPARTMENTS_MEDI  LIVINGAREA_MEDI  \\\n",
       "0          0.1250         0.0375                 0.0205           0.0193   \n",
       "1          0.3333         0.0132                 0.0787           0.0558   \n",
       "2             NaN            NaN                    NaN              NaN   \n",
       "3             NaN            NaN                    NaN              NaN   \n",
       "4             NaN            NaN                    NaN              NaN   \n",
       "\n",
       "   NONLIVINGAPARTMENTS_MEDI  NONLIVINGAREA_MEDI FONDKAPREMONT_MODE  \\\n",
       "0                    0.0000                0.00   reg oper account   \n",
       "1                    0.0039                0.01   reg oper account   \n",
       "2                       NaN                 NaN                NaN   \n",
       "3                       NaN                 NaN                NaN   \n",
       "4                       NaN                 NaN                NaN   \n",
       "\n",
       "   HOUSETYPE_MODE  TOTALAREA_MODE WALLSMATERIAL_MODE EMERGENCYSTATE_MODE  \\\n",
       "0  block of flats          0.0149       Stone, brick                  No   \n",
       "1  block of flats          0.0714              Block                  No   \n",
       "2             NaN             NaN                NaN                 NaN   \n",
       "3             NaN             NaN                NaN                 NaN   \n",
       "4             NaN             NaN                NaN                 NaN   \n",
       "\n",
       "   OBS_30_CNT_SOCIAL_CIRCLE  DEF_30_CNT_SOCIAL_CIRCLE  \\\n",
       "0                       2.0                       2.0   \n",
       "1                       1.0                       0.0   \n",
       "2                       0.0                       0.0   \n",
       "3                       2.0                       0.0   \n",
       "4                       0.0                       0.0   \n",
       "\n",
       "   OBS_60_CNT_SOCIAL_CIRCLE  DEF_60_CNT_SOCIAL_CIRCLE  DAYS_LAST_PHONE_CHANGE  \\\n",
       "0                       2.0                       2.0                 -1134.0   \n",
       "1                       1.0                       0.0                  -828.0   \n",
       "2                       0.0                       0.0                  -815.0   \n",
       "3                       2.0                       0.0                  -617.0   \n",
       "4                       0.0                       0.0                 -1106.0   \n",
       "\n",
       "   FLAG_DOCUMENT_2  FLAG_DOCUMENT_3  FLAG_DOCUMENT_4  FLAG_DOCUMENT_5  \\\n",
       "0                0                1                0                0   \n",
       "1                0                1                0                0   \n",
       "2                0                0                0                0   \n",
       "3                0                1                0                0   \n",
       "4                0                0                0                0   \n",
       "\n",
       "   FLAG_DOCUMENT_6  FLAG_DOCUMENT_7  FLAG_DOCUMENT_8  FLAG_DOCUMENT_9  \\\n",
       "0                0                0                0                0   \n",
       "1                0                0                0                0   \n",
       "2                0                0                0                0   \n",
       "3                0                0                0                0   \n",
       "4                0                0                1                0   \n",
       "\n",
       "   FLAG_DOCUMENT_10  FLAG_DOCUMENT_11  FLAG_DOCUMENT_12  FLAG_DOCUMENT_13  \\\n",
       "0                 0                 0                 0                 0   \n",
       "1                 0                 0                 0                 0   \n",
       "2                 0                 0                 0                 0   \n",
       "3                 0                 0                 0                 0   \n",
       "4                 0                 0                 0                 0   \n",
       "\n",
       "   FLAG_DOCUMENT_14  FLAG_DOCUMENT_15  FLAG_DOCUMENT_16  FLAG_DOCUMENT_17  \\\n",
       "0                 0                 0                 0                 0   \n",
       "1                 0                 0                 0                 0   \n",
       "2                 0                 0                 0                 0   \n",
       "3                 0                 0                 0                 0   \n",
       "4                 0                 0                 0                 0   \n",
       "\n",
       "   FLAG_DOCUMENT_18  FLAG_DOCUMENT_19  FLAG_DOCUMENT_20  FLAG_DOCUMENT_21  \\\n",
       "0                 0                 0                 0                 0   \n",
       "1                 0                 0                 0                 0   \n",
       "2                 0                 0                 0                 0   \n",
       "3                 0                 0                 0                 0   \n",
       "4                 0                 0                 0                 0   \n",
       "\n",
       "   AMT_REQ_CREDIT_BUREAU_HOUR  AMT_REQ_CREDIT_BUREAU_DAY  \\\n",
       "0                         0.0                        0.0   \n",
       "1                         0.0                        0.0   \n",
       "2                         0.0                        0.0   \n",
       "3                         NaN                        NaN   \n",
       "4                         0.0                        0.0   \n",
       "\n",
       "   AMT_REQ_CREDIT_BUREAU_WEEK  AMT_REQ_CREDIT_BUREAU_MON  \\\n",
       "0                         0.0                        0.0   \n",
       "1                         0.0                        0.0   \n",
       "2                         0.0                        0.0   \n",
       "3                         NaN                        NaN   \n",
       "4                         0.0                        0.0   \n",
       "\n",
       "   AMT_REQ_CREDIT_BUREAU_QRT  AMT_REQ_CREDIT_BUREAU_YEAR  \n",
       "0                        0.0                         1.0  \n",
       "1                        0.0                         0.0  \n",
       "2                        0.0                         0.0  \n",
       "3                        NaN                         NaN  \n",
       "4                        0.0                         0.0  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Aperçu des premières lignes\n",
    "print(\"=== Premières lignes du dataset ===\")\n",
    "app_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "783dbd49",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=== Informations sur le dataset ===\n",
      "Nombre de lignes : 307,511\n",
      "Nombre de colonnes : 122\n",
      "\n",
      "Mémoire utilisée : 504.99 MB\n"
     ]
    }
   ],
   "source": [
    "# Informations générales sur le dataset\n",
    "print(\"=== Informations sur le dataset ===\")\n",
    "print(f\"Nombre de lignes : {app_train.shape[0]:,}\")\n",
    "print(f\"Nombre de colonnes : {app_train.shape[1]:,}\")\n",
    "print(f\"\\nMémoire utilisée : {app_train.memory_usage(deep=True).sum() / 1024**2:.2f} MB\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "d8959dd1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=== Répartition des types de données ===\n",
      "float64    65\n",
      "int64      41\n",
      "object     16\n",
      "Name: count, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# Types de données\n",
    "print(\"=== Répartition des types de données ===\")\n",
    "print(app_train.dtypes.value_counts())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ded0b5d",
   "metadata": {},
   "source": [
    "## 4. Analyse de la Variable Cible (TARGET)\n",
    "\n",
    "La variable TARGET indique si un client a eu des difficultés de paiement :\n",
    "- **0** : Pas de difficulté de paiement\n",
    "- **1** : Difficulté de paiement\n",
    "\n",
    "Cette analyse nous permet de comprendre le **déséquilibre des classes**, crucial pour la modélisation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "1a0bf184",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=== Distribution de la Variable Cible ===\n",
      "\n",
      "Nombre de clients par catégorie :\n",
      "  - Sans difficulté (0) : 282,686 (91.93%)\n",
      "  - Avec difficulté (1) : 24,825 (8.07%)\n",
      "\n",
      "⚠️  Ratio de déséquilibre : 11.4:1\n",
      "    → Les classes sont très déséquilibrées, il faudra en tenir compte dans la modélisation\n"
     ]
    }
   ],
   "source": [
    "# Distribution de la variable cible\n",
    "print(\"=== Distribution de la Variable Cible ===\")\n",
    "target_counts = app_train['TARGET'].value_counts()\n",
    "target_pct = app_train['TARGET'].value_counts(normalize=True) * 100\n",
    "\n",
    "print(f\"\\nNombre de clients par catégorie :\")\n",
    "print(f\"  - Sans difficulté (0) : {target_counts[0]:,} ({target_pct[0]:.2f}%)\")\n",
    "print(f\"  - Avec difficulté (1) : {target_counts[1]:,} ({target_pct[1]:.2f}%)\")\n",
    "\n",
    "ratio = target_counts[0] / target_counts[1]\n",
    "print(f\"\\n⚠️  Ratio de déséquilibre : {ratio:.1f}:1\")\n",
    "print(\"    → Les classes sont très déséquilibrées, il faudra en tenir compte dans la modélisation\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "00de9f27",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1400x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "📊 Observation : Environ 92% des clients n'ont pas de difficultés, 8% en ont.\n"
     ]
    }
   ],
   "source": [
    "# Visualisation de la distribution de TARGET\n",
    "fig, axes = plt.subplots(1, 2, figsize=(14, 5))\n",
    "\n",
    "# Graphique en barres\n",
    "target_counts.plot(kind='bar', ax=axes[0], color=['#2ecc71', '#e74c3c'])\n",
    "axes[0].set_title('Distribution de la Variable Cible', fontsize=14, fontweight='bold')\n",
    "axes[0].set_xlabel('TARGET')\n",
    "axes[0].set_ylabel('Nombre de clients')\n",
    "axes[0].set_xticklabels(['Pas de difficulté (0)', 'Difficulté (1)'], rotation=0)\n",
    "axes[0].grid(axis='y', alpha=0.3)\n",
    "\n",
    "# Ajout des pourcentages sur les barres\n",
    "for i, (count, pct) in enumerate(zip(target_counts, target_pct)):\n",
    "    axes[0].text(i, count + 5000, f'{pct:.1f}%', ha='center', fontweight='bold')\n",
    "\n",
    "# Graphique en camembert\n",
    "axes[1].pie(target_counts, labels=['Pas de difficulté (0)', 'Difficulté (1)'], \n",
    "            autopct='%1.1f%%', startangle=90, colors=['#2ecc71', '#e74c3c'])\n",
    "axes[1].set_title('Répartition en Pourcentage', fontsize=14, fontweight='bold')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "print(\"📊 Observation : Environ 92% des clients n'ont pas de difficultés, 8% en ont.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e8ef678c",
   "metadata": {},
   "source": [
    "## 5. Analyse des Valeurs Manquantes\n",
    "\n",
    "Les valeurs manquantes peuvent indiquer :\n",
    "- Des informations non collectées\n",
    "- Des données non applicables pour certains clients\n",
    "- Des problèmes de qualité des données\n",
    "\n",
    "Créons une fonction pour analyser systématiquement les valeurs manquantes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "9682e974",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Le dataset contient 122 colonnes.\n",
      "67 colonnes ont des valeurs manquantes.\n"
     ]
    }
   ],
   "source": [
    "def missing_values_table(df):\n",
    "    \"\"\"\n",
    "    Calcule le nombre et le pourcentage de valeurs manquantes pour chaque colonne.\n",
    "    \n",
    "    Args:\n",
    "        df: DataFrame à analyser\n",
    "        \n",
    "    Returns:\n",
    "        DataFrame avec les colonnes ayant des valeurs manquantes, triées par pourcentage décroissant\n",
    "    \"\"\"\n",
    "    # Nombre de valeurs manquantes\n",
    "    mis_val = df.isnull().sum()\n",
    "    \n",
    "    # Pourcentage de valeurs manquantes\n",
    "    mis_val_percent = 100 * mis_val / len(df)\n",
    "    \n",
    "    # Création du tableau de résultats\n",
    "    mis_val_table = pd.concat([mis_val, mis_val_percent], axis=1)\n",
    "    mis_val_table.columns = ['Valeurs Manquantes', 'Pourcentage (%)']\n",
    "    \n",
    "    # Tri par pourcentage décroissant et filtrage (seulement les colonnes avec des NaN)\n",
    "    mis_val_table = mis_val_table[mis_val_table['Valeurs Manquantes'] > 0].sort_values(\n",
    "        'Pourcentage (%)', ascending=False\n",
    "    )\n",
    "    \n",
    "    # Affichage du résumé\n",
    "    print(f\"Le dataset contient {df.shape[1]} colonnes.\")\n",
    "    print(f\"{mis_val_table.shape[0]} colonnes ont des valeurs manquantes.\")\n",
    "    \n",
    "    return mis_val_table\n",
    "\n",
    "# Application de la fonction\n",
    "missing_train = missing_values_table(app_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "8813d071",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=== Top 20 des Colonnes avec le Plus de Valeurs Manquantes ===\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Valeurs Manquantes</th>\n",
       "      <th>Pourcentage (%)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>COMMONAREA_MEDI</th>\n",
       "      <td>214865</td>\n",
       "      <td>69.872297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>COMMONAREA_MODE</th>\n",
       "      <td>214865</td>\n",
       "      <td>69.872297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>COMMONAREA_AVG</th>\n",
       "      <td>214865</td>\n",
       "      <td>69.872297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NONLIVINGAPARTMENTS_MODE</th>\n",
       "      <td>213514</td>\n",
       "      <td>69.432963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NONLIVINGAPARTMENTS_MEDI</th>\n",
       "      <td>213514</td>\n",
       "      <td>69.432963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NONLIVINGAPARTMENTS_AVG</th>\n",
       "      <td>213514</td>\n",
       "      <td>69.432963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FONDKAPREMONT_MODE</th>\n",
       "      <td>210295</td>\n",
       "      <td>68.386172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LIVINGAPARTMENTS_AVG</th>\n",
       "      <td>210199</td>\n",
       "      <td>68.354953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LIVINGAPARTMENTS_MEDI</th>\n",
       "      <td>210199</td>\n",
       "      <td>68.354953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LIVINGAPARTMENTS_MODE</th>\n",
       "      <td>210199</td>\n",
       "      <td>68.354953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FLOORSMIN_MEDI</th>\n",
       "      <td>208642</td>\n",
       "      <td>67.848630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FLOORSMIN_MODE</th>\n",
       "      <td>208642</td>\n",
       "      <td>67.848630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FLOORSMIN_AVG</th>\n",
       "      <td>208642</td>\n",
       "      <td>67.848630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YEARS_BUILD_MODE</th>\n",
       "      <td>204488</td>\n",
       "      <td>66.497784</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YEARS_BUILD_MEDI</th>\n",
       "      <td>204488</td>\n",
       "      <td>66.497784</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YEARS_BUILD_AVG</th>\n",
       "      <td>204488</td>\n",
       "      <td>66.497784</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OWN_CAR_AGE</th>\n",
       "      <td>202929</td>\n",
       "      <td>65.990810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LANDAREA_AVG</th>\n",
       "      <td>182590</td>\n",
       "      <td>59.376738</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LANDAREA_MEDI</th>\n",
       "      <td>182590</td>\n",
       "      <td>59.376738</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LANDAREA_MODE</th>\n",
       "      <td>182590</td>\n",
       "      <td>59.376738</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          Valeurs Manquantes  Pourcentage (%)\n",
       "COMMONAREA_MEDI                       214865        69.872297\n",
       "COMMONAREA_MODE                       214865        69.872297\n",
       "COMMONAREA_AVG                        214865        69.872297\n",
       "NONLIVINGAPARTMENTS_MODE              213514        69.432963\n",
       "NONLIVINGAPARTMENTS_MEDI              213514        69.432963\n",
       "NONLIVINGAPARTMENTS_AVG               213514        69.432963\n",
       "FONDKAPREMONT_MODE                    210295        68.386172\n",
       "LIVINGAPARTMENTS_AVG                  210199        68.354953\n",
       "LIVINGAPARTMENTS_MEDI                 210199        68.354953\n",
       "LIVINGAPARTMENTS_MODE                 210199        68.354953\n",
       "FLOORSMIN_MEDI                        208642        67.848630\n",
       "FLOORSMIN_MODE                        208642        67.848630\n",
       "FLOORSMIN_AVG                         208642        67.848630\n",
       "YEARS_BUILD_MODE                      204488        66.497784\n",
       "YEARS_BUILD_MEDI                      204488        66.497784\n",
       "YEARS_BUILD_AVG                       204488        66.497784\n",
       "OWN_CAR_AGE                           202929        65.990810\n",
       "LANDAREA_AVG                          182590        59.376738\n",
       "LANDAREA_MEDI                         182590        59.376738\n",
       "LANDAREA_MODE                         182590        59.376738"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Affichage des 20 colonnes avec le plus de valeurs manquantes\n",
    "print(\"=== Top 20 des Colonnes avec le Plus de Valeurs Manquantes ===\\n\")\n",
    "missing_train.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "ff7f1560",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "⚠️  49 colonnes ont plus de 40% de valeurs manquantes\n",
      "    → Ces colonnes pourraient nécessiter une imputation sophistiquée ou être exclues\n"
     ]
    }
   ],
   "source": [
    "# Visualisation des valeurs manquantes\n",
    "fig, ax = plt.subplots(figsize=(12, 8))\n",
    "\n",
    "# Sélection des 20 colonnes avec le plus de valeurs manquantes\n",
    "top_missing = missing_train.head(20)\n",
    "\n",
    "# Création du graphique en barres horizontales\n",
    "bars = ax.barh(range(len(top_missing)), top_missing['Pourcentage (%)'], color='coral')\n",
    "ax.set_yticks(range(len(top_missing)))\n",
    "ax.set_yticklabels(top_missing.index)\n",
    "ax.set_xlabel('Pourcentage de Valeurs Manquantes (%)', fontsize=12)\n",
    "ax.set_title('Top 20 des Variables avec le Plus de Valeurs Manquantes', \n",
    "             fontsize=14, fontweight='bold', pad=20)\n",
    "ax.grid(axis='x', alpha=0.3)\n",
    "\n",
    "# Ajout des valeurs à la fin des barres\n",
    "for i, (idx, row) in enumerate(top_missing.iterrows()):\n",
    "    ax.text(row['Pourcentage (%)'] + 1, i, f\"{row['Pourcentage (%)']:.1f}%\", \n",
    "            va='center', fontsize=9)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "print(f\"\\n⚠️  {(missing_train['Pourcentage (%)'] > 40).sum()} colonnes ont plus de 40% de valeurs manquantes\")\n",
    "print(\"    → Ces colonnes pourraient nécessiter une imputation sophistiquée ou être exclues\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e7d70e03",
   "metadata": {},
   "source": [
    "## 6. Analyse des Types de Variables\n",
    "\n",
    "Séparons les variables numériques et catégorielles pour mieux comprendre la structure des données."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "818af794",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=== Types de Variables ===\n",
      "\n",
      "Variables Numériques : 106\n",
      "Variables Catégorielles : 16\n",
      "\n",
      "--- Variables Catégorielles ---\n",
      "  • NAME_CONTRACT_TYPE: 2 valeurs uniques\n",
      "  • CODE_GENDER: 3 valeurs uniques\n",
      "  • FLAG_OWN_CAR: 2 valeurs uniques\n",
      "  • FLAG_OWN_REALTY: 2 valeurs uniques\n",
      "  • NAME_TYPE_SUITE: 7 valeurs uniques\n",
      "  • NAME_INCOME_TYPE: 8 valeurs uniques\n",
      "  • NAME_EDUCATION_TYPE: 5 valeurs uniques\n",
      "  • NAME_FAMILY_STATUS: 6 valeurs uniques\n",
      "  • NAME_HOUSING_TYPE: 6 valeurs uniques\n",
      "  • OCCUPATION_TYPE: 18 valeurs uniques\n",
      "  • WEEKDAY_APPR_PROCESS_START: 7 valeurs uniques\n",
      "  • ORGANIZATION_TYPE: 58 valeurs uniques\n",
      "  • FONDKAPREMONT_MODE: 4 valeurs uniques\n",
      "  • HOUSETYPE_MODE: 3 valeurs uniques\n",
      "  • WALLSMATERIAL_MODE: 7 valeurs uniques\n",
      "  • EMERGENCYSTATE_MODE: 2 valeurs uniques\n"
     ]
    }
   ],
   "source": [
    "# Identification des types de colonnes\n",
    "numeric_columns = app_train.select_dtypes(include=['int64', 'float64']).columns.tolist()\n",
    "categorical_columns = app_train.select_dtypes(include=['object']).columns.tolist()\n",
    "\n",
    "print(\"=== Types de Variables ===\")\n",
    "print(f\"\\nVariables Numériques : {len(numeric_columns)}\")\n",
    "print(f\"Variables Catégorielles : {len(categorical_columns)}\")\n",
    "\n",
    "print(\"\\n--- Variables Catégorielles ---\")\n",
    "for col in categorical_columns:\n",
    "    n_unique = app_train[col].nunique()\n",
    "    print(f\"  • {col}: {n_unique} valeurs uniques\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "7db0979e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=== Distribution des Variables Catégorielles ===\n",
      "\n",
      "\n",
      "NAME_CONTRACT_TYPE:\n",
      "NAME_CONTRACT_TYPE\n",
      "Cash loans         278232\n",
      "Revolving loans     29279\n",
      "Name: count, dtype: int64\n",
      "--------------------------------------------------\n",
      "\n",
      "CODE_GENDER:\n",
      "CODE_GENDER\n",
      "F      202448\n",
      "M      105059\n",
      "XNA         4\n",
      "Name: count, dtype: int64\n",
      "--------------------------------------------------\n",
      "\n",
      "FLAG_OWN_CAR:\n",
      "FLAG_OWN_CAR\n",
      "N    202924\n",
      "Y    104587\n",
      "Name: count, dtype: int64\n",
      "--------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "# Analyse des variables catégorielles\n",
    "print(\"=== Distribution des Variables Catégorielles ===\\n\")\n",
    "\n",
    "for col in categorical_columns[:3]:  # Affichons les 3 premières pour l'exemple\n",
    "    print(f\"\\n{col}:\")\n",
    "    print(app_train[col].value_counts())\n",
    "    print(\"-\" * 50)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1f3c9102",
   "metadata": {},
   "source": [
    "## 7. Analyse des Corrélations avec TARGET\n",
    "\n",
    "Identifions les variables numériques les plus corrélées avec la variable cible.\n",
    "Une **corrélation positive** indique que des valeurs élevées sont associées à plus de difficultés de paiement.\n",
    "Une **corrélation négative** indique que des valeurs élevées sont associées à moins de difficultés."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "29b7cbde",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=== Top 15 Corrélations POSITIVES avec TARGET ===\n",
      "(Valeurs élevées → Plus de risque de défaut)\n",
      "\n",
      "DAYS_BIRTH                     0.078239\n",
      "REGION_RATING_CLIENT_W_CITY    0.060893\n",
      "REGION_RATING_CLIENT           0.058899\n",
      "DAYS_LAST_PHONE_CHANGE         0.055218\n",
      "DAYS_ID_PUBLISH                0.051457\n",
      "REG_CITY_NOT_WORK_CITY         0.050994\n",
      "FLAG_EMP_PHONE                 0.045982\n",
      "REG_CITY_NOT_LIVE_CITY         0.044395\n",
      "FLAG_DOCUMENT_3                0.044346\n",
      "DAYS_REGISTRATION              0.041975\n",
      "OWN_CAR_AGE                    0.037612\n",
      "LIVE_CITY_NOT_WORK_CITY        0.032518\n",
      "DEF_30_CNT_SOCIAL_CIRCLE       0.032248\n",
      "DEF_60_CNT_SOCIAL_CIRCLE       0.031276\n",
      "FLAG_WORK_PHONE                0.028524\n",
      "Name: TARGET, dtype: float64\n",
      "\n",
      "\n",
      "=== Top 15 Corrélations NÉGATIVES avec TARGET ===\n",
      "(Valeurs élevées → Moins de risque de défaut)\n",
      "\n",
      "LIVINGAREA_MEDI              -0.032739\n",
      "LIVINGAREA_AVG               -0.032997\n",
      "FLOORSMIN_MEDI               -0.033394\n",
      "FLOORSMIN_AVG                -0.033614\n",
      "ELEVATORS_MEDI               -0.033863\n",
      "ELEVATORS_AVG                -0.034199\n",
      "REGION_POPULATION_RELATIVE   -0.037227\n",
      "AMT_GOODS_PRICE              -0.039645\n",
      "FLOORSMAX_MODE               -0.043226\n",
      "FLOORSMAX_MEDI               -0.043768\n",
      "FLOORSMAX_AVG                -0.044003\n",
      "DAYS_EMPLOYED                -0.044932\n",
      "EXT_SOURCE_1                 -0.155317\n",
      "EXT_SOURCE_2                 -0.160472\n",
      "EXT_SOURCE_3                 -0.178919\n",
      "Name: TARGET, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "# Calcul des corrélations avec TARGET (uniquement pour les variables numériques)\n",
    "correlations = app_train.select_dtypes(include=[np.number]).corr()['TARGET'].sort_values(ascending=False)\n",
    "\n",
    "# Suppression de TARGET lui-même\n",
    "correlations = correlations.drop('TARGET')\n",
    "\n",
    "print(\"=== Top 15 Corrélations POSITIVES avec TARGET ===\")\n",
    "print(\"(Valeurs élevées → Plus de risque de défaut)\\n\")\n",
    "print(correlations.head(15))\n",
    "\n",
    "print(\"\\n\\n=== Top 15 Corrélations NÉGATIVES avec TARGET ===\")\n",
    "print(\"(Valeurs élevées → Moins de risque de défaut)\\n\")\n",
    "print(correlations.tail(15))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "ef928a17",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 1600x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "📊 Observation clé : Les variables EXT_SOURCE ont les corrélations négatives les plus fortes\n",
      "    → Plus les scores EXT_SOURCE sont élevés, moins il y a de risque de défaut\n"
     ]
    }
   ],
   "source": [
    "# Visualisation des corrélations les plus fortes\n",
    "fig, axes = plt.subplots(1, 2, figsize=(16, 6))\n",
    "\n",
    "# Top 10 corrélations positives\n",
    "top_positive = correlations.head(10)\n",
    "axes[0].barh(range(len(top_positive)), top_positive.values, color='#e74c3c')\n",
    "axes[0].set_yticks(range(len(top_positive)))\n",
    "axes[0].set_yticklabels(top_positive.index, fontsize=10)\n",
    "axes[0].set_xlabel('Corrélation avec TARGET', fontsize=11)\n",
    "axes[0].set_title('Top 10 Corrélations Positives\\n(Augmentent le risque)', \n",
    "                  fontsize=13, fontweight='bold')\n",
    "axes[0].grid(axis='x', alpha=0.3)\n",
    "axes[0].invert_yaxis()\n",
    "\n",
    "# Top 10 corrélations négatives\n",
    "top_negative = correlations.tail(10).sort_values()\n",
    "axes[1].barh(range(len(top_negative)), top_negative.values, color='#2ecc71')\n",
    "axes[1].set_yticks(range(len(top_negative)))\n",
    "axes[1].set_yticklabels(top_negative.index, fontsize=10)\n",
    "axes[1].set_xlabel('Corrélation avec TARGET', fontsize=11)\n",
    "axes[1].set_title('Top 10 Corrélations Négatives\\n(Réduisent le risque)', \n",
    "                  fontsize=13, fontweight='bold')\n",
    "axes[1].grid(axis='x', alpha=0.3)\n",
    "axes[1].invert_yaxis()\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "print(\"\\n📊 Observation clé : Les variables EXT_SOURCE ont les corrélations négatives les plus fortes\")\n",
    "print(\"    → Plus les scores EXT_SOURCE sont élevés, moins il y a de risque de défaut\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a38fc239",
   "metadata": {},
   "source": [
    "## 8. Analyse de l'Âge (DAYS_BIRTH)\n",
    "\n",
    "La variable `DAYS_BIRTH` est négative (nombre de jours avant la demande).\n",
    "Convertissons-la en années pour une meilleure interprétation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "44b8c5f3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=== Statistiques sur l'Âge des Clients ===\n",
      "count    307511.000000\n",
      "mean         43.936973\n",
      "std          11.956133\n",
      "min          20.517808\n",
      "25%          34.008219\n",
      "50%          43.150685\n",
      "75%          53.923288\n",
      "max          69.120548\n",
      "Name: YEARS_BIRTH, dtype: float64\n",
      "\n",
      "• Âge moyen : 43.9 ans\n",
      "• Âge médian : 43.2 ans\n",
      "• Âge min : 20.5 ans\n",
      "• Âge max : 69.1 ans\n"
     ]
    }
   ],
   "source": [
    "# Conversion de DAYS_BIRTH en années\n",
    "app_train['YEARS_BIRTH'] = abs(app_train['DAYS_BIRTH']) / 365\n",
    "\n",
    "print(\"=== Statistiques sur l'Âge des Clients ===\")\n",
    "print(app_train['YEARS_BIRTH'].describe())\n",
    "print(f\"\\n• Âge moyen : {app_train['YEARS_BIRTH'].mean():.1f} ans\")\n",
    "print(f\"• Âge médian : {app_train['YEARS_BIRTH'].median():.1f} ans\")\n",
    "print(f\"• Âge min : {app_train['YEARS_BIRTH'].min():.1f} ans\")\n",
    "print(f\"• Âge max : {app_train['YEARS_BIRTH'].max():.1f} ans\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "7a5f941d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1600x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "📊 Âge moyen selon le statut :\n",
      "  • Sans difficulté : 44.2 ans\n",
      "  • Avec difficulté : 40.8 ans\n",
      "  • Différence : 3.4 ans\n",
      "\n",
      "💡 Les clients plus jeunes ont tendance à avoir légèrement plus de difficultés de paiement\n"
     ]
    }
   ],
   "source": [
    "# Distribution de l'âge selon le statut de défaut\n",
    "fig, axes = plt.subplots(1, 2, figsize=(16, 5))\n",
    "\n",
    "# Distribution globale\n",
    "axes[0].hist(app_train['YEARS_BIRTH'], bins=50, edgecolor='black', alpha=0.7, color='skyblue')\n",
    "axes[0].set_xlabel('Âge (années)', fontsize=12)\n",
    "axes[0].set_ylabel('Nombre de clients', fontsize=12)\n",
    "axes[0].set_title('Distribution de l\\'Âge des Clients', fontsize=14, fontweight='bold')\n",
    "axes[0].grid(axis='y', alpha=0.3)\n",
    "axes[0].axvline(app_train['YEARS_BIRTH'].mean(), color='red', linestyle='--', \n",
    "                linewidth=2, label=f'Moyenne: {app_train[\"YEARS_BIRTH\"].mean():.1f} ans')\n",
    "axes[0].legend()\n",
    "\n",
    "# KDE par statut TARGET\n",
    "sns.kdeplot(data=app_train[app_train['TARGET'] == 0]['YEARS_BIRTH'], \n",
    "            ax=axes[1], label='Pas de difficulté (TARGET=0)', shade=True, color='#2ecc71')\n",
    "sns.kdeplot(data=app_train[app_train['TARGET'] == 1]['YEARS_BIRTH'], \n",
    "            ax=axes[1], label='Difficulté (TARGET=1)', shade=True, color='#e74c3c')\n",
    "axes[1].set_xlabel('Âge (années)', fontsize=12)\n",
    "axes[1].set_ylabel('Densité', fontsize=12)\n",
    "axes[1].set_title('Distribution de l\\'Âge selon le Statut de Défaut', fontsize=14, fontweight='bold')\n",
    "axes[1].legend()\n",
    "axes[1].grid(alpha=0.3)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "# Calcul des moyennes par groupe\n",
    "mean_age_no_default = app_train[app_train['TARGET'] == 0]['YEARS_BIRTH'].mean()\n",
    "mean_age_default = app_train[app_train['TARGET'] == 1]['YEARS_BIRTH'].mean()\n",
    "\n",
    "print(f\"\\n📊 Âge moyen selon le statut :\")\n",
    "print(f\"  • Sans difficulté : {mean_age_no_default:.1f} ans\")\n",
    "print(f\"  • Avec difficulté : {mean_age_default:.1f} ans\")\n",
    "print(f\"  • Différence : {abs(mean_age_no_default - mean_age_default):.1f} ans\")\n",
    "print(\"\\n💡 Les clients plus jeunes ont tendance à avoir légèrement plus de difficultés de paiement\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb014e3d",
   "metadata": {},
   "source": [
    "## 9. Détection d'Anomalies - DAYS_EMPLOYED\n",
    "\n",
    "Examinons la variable `DAYS_EMPLOYED` (nombre de jours d'emploi avant la demande).\n",
    "Des valeurs anormales peuvent indiquer des cas spéciaux ou des erreurs de données."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "f08ffc80",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=== Statistiques sur DAYS_EMPLOYED ===\n",
      "count    307511.000000\n",
      "mean      63815.045904\n",
      "std      141275.766519\n",
      "min      -17912.000000\n",
      "25%       -2760.000000\n",
      "50%       -1213.000000\n",
      "75%        -289.000000\n",
      "max      365243.000000\n",
      "Name: DAYS_EMPLOYED, dtype: float64\n",
      "\n",
      "• Valeur maximale : 365243\n",
      "• Nombre de valeurs = 365243 : 55,374\n",
      "  → Représente 18.01% des données\n",
      "\n",
      "⚠️  La valeur 365243 (~1000 ans) est clairement une anomalie\n",
      "    → Il s'agit probablement d'un flag pour indiquer une situation particulière\n",
      "       (ex: retraité, sans emploi, etc.)\n"
     ]
    }
   ],
   "source": [
    "# Examen de DAYS_EMPLOYED\n",
    "print(\"=== Statistiques sur DAYS_EMPLOYED ===\")\n",
    "print(app_train['DAYS_EMPLOYED'].describe())\n",
    "\n",
    "# Vérification des valeurs extrêmes\n",
    "print(f\"\\n• Valeur maximale : {app_train['DAYS_EMPLOYED'].max()}\")\n",
    "print(f\"• Nombre de valeurs = 365243 : {(app_train['DAYS_EMPLOYED'] == 365243).sum():,}\")\n",
    "print(f\"  → Représente {(app_train['DAYS_EMPLOYED'] == 365243).mean() * 100:.2f}% des données\")\n",
    "\n",
    "print(\"\\n⚠️  La valeur 365243 (~1000 ans) est clairement une anomalie\")\n",
    "print(\"    → Il s'agit probablement d'un flag pour indiquer une situation particulière\")\n",
    "print(\"       (ex: retraité, sans emploi, etc.)\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "c9750c86",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 1600x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualisation de DAYS_EMPLOYED\n",
    "fig, axes = plt.subplots(1, 2, figsize=(16, 5))\n",
    "\n",
    "# Histogramme avec l'anomalie\n",
    "axes[0].hist(app_train['DAYS_EMPLOYED'], bins=50, edgecolor='black', alpha=0.7, color='coral')\n",
    "axes[0].set_xlabel('DAYS_EMPLOYED', fontsize=12)\n",
    "axes[0].set_ylabel('Nombre de clients', fontsize=12)\n",
    "axes[0].set_title('Distribution de DAYS_EMPLOYED (avec anomalie)', fontsize=14, fontweight='bold')\n",
    "axes[0].grid(axis='y', alpha=0.3)\n",
    "\n",
    "# Histogramme sans l'anomalie\n",
    "app_train_no_anom = app_train[app_train['DAYS_EMPLOYED'] != 365243]\n",
    "axes[1].hist(app_train_no_anom['DAYS_EMPLOYED'], bins=50, edgecolor='black', alpha=0.7, color='skyblue')\n",
    "axes[1].set_xlabel('DAYS_EMPLOYED', fontsize=12)\n",
    "axes[1].set_ylabel('Nombre de clients', fontsize=12)\n",
    "axes[1].set_title('Distribution de DAYS_EMPLOYED (sans anomalie)', fontsize=14, fontweight='bold')\n",
    "axes[1].grid(axis='y', alpha=0.3)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "a389109a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=== Impact de l'Anomalie sur le Taux de Défaut ===\n",
      "\n",
      "Taux de défaut avec anomalie (DAYS_EMPLOYED = 365243) : 5.40%\n",
      "Taux de défaut sans anomalie : 8.66%\n",
      "Différence : 3.26 points de pourcentage\n",
      "\n",
      "✓ Flag 'DAYS_EMPLOYED_ANOM' créé pour capturer cette information\n",
      "✓ Cette variable pourra être utilisée dans la modélisation\n",
      "\n",
      "✓ Valeurs 365243 remplacées par NaN dans DAYS_EMPLOYED\n"
     ]
    }
   ],
   "source": [
    "# Création d'un flag pour l'anomalie et traitement\n",
    "app_train['DAYS_EMPLOYED_ANOM'] = app_train['DAYS_EMPLOYED'] == 365243\n",
    "app_test['DAYS_EMPLOYED_ANOM'] = app_test['DAYS_EMPLOYED'] == 365243\n",
    "\n",
    "# Comparaison du taux de défaut\n",
    "print(\"=== Impact de l'Anomalie sur le Taux de Défaut ===\\n\")\n",
    "\n",
    "anom_default_rate = app_train[app_train['DAYS_EMPLOYED_ANOM']]['TARGET'].mean() * 100\n",
    "normal_default_rate = app_train[~app_train['DAYS_EMPLOYED_ANOM']]['TARGET'].mean() * 100\n",
    "\n",
    "print(f\"Taux de défaut avec anomalie (DAYS_EMPLOYED = 365243) : {anom_default_rate:.2f}%\")\n",
    "print(f\"Taux de défaut sans anomalie : {normal_default_rate:.2f}%\")\n",
    "print(f\"Différence : {abs(anom_default_rate - normal_default_rate):.2f} points de pourcentage\")\n",
    "\n",
    "print(\"\\n✓ Flag 'DAYS_EMPLOYED_ANOM' créé pour capturer cette information\")\n",
    "print(\"✓ Cette variable pourra être utilisée dans la modélisation\")\n",
    "\n",
    "# Remplacement de l'anomalie par NaN pour les futures analyses\n",
    "app_train['DAYS_EMPLOYED'].replace({365243: np.nan}, inplace=True)\n",
    "app_test['DAYS_EMPLOYED'].replace({365243: np.nan}, inplace=True)\n",
    "\n",
    "print(\"\\n✓ Valeurs 365243 remplacées par NaN dans DAYS_EMPLOYED\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d3e8e1c4",
   "metadata": {},
   "source": [
    "## 10. Analyse des Variables EXT_SOURCE\n",
    "\n",
    "Les variables `EXT_SOURCE_1`, `EXT_SOURCE_2`, et `EXT_SOURCE_3` sont normalisées entre 0 et 1.\n",
    "Elles proviennent de sources externes et sont très prédictives du risque de défaut."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "06c852f0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=== Statistiques sur les Variables EXT_SOURCE ===\n",
      "\n",
      "        EXT_SOURCE_1  EXT_SOURCE_2   EXT_SOURCE_3\n",
      "count  134133.000000  3.068510e+05  246546.000000\n",
      "mean        0.502130  5.143927e-01       0.510853\n",
      "std         0.211062  1.910602e-01       0.194844\n",
      "min         0.014568  8.173617e-08       0.000527\n",
      "25%         0.334007  3.924574e-01       0.370650\n",
      "50%         0.505998  5.659614e-01       0.535276\n",
      "75%         0.675053  6.636171e-01       0.669057\n",
      "max         0.962693  8.549997e-01       0.896010\n",
      "\n",
      "=== Valeurs Manquantes ===\n",
      "EXT_SOURCE_1: 56.38%\n",
      "EXT_SOURCE_2: 0.21%\n",
      "EXT_SOURCE_3: 19.83%\n"
     ]
    }
   ],
   "source": [
    "# Examen des variables EXT_SOURCE\n",
    "ext_source_cols = ['EXT_SOURCE_1', 'EXT_SOURCE_2', 'EXT_SOURCE_3']\n",
    "\n",
    "print(\"=== Statistiques sur les Variables EXT_SOURCE ===\\n\")\n",
    "print(app_train[ext_source_cols].describe())\n",
    "\n",
    "print(\"\\n=== Valeurs Manquantes ===\")\n",
    "for col in ext_source_cols:\n",
    "    missing_pct = app_train[col].isnull().mean() * 100\n",
    "    print(f\"{col}: {missing_pct:.2f}%\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "08934de5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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86vZERKoy5VZ5U26Vk3KrnCpbbgWwfft2EhIS+Oijj3juuef45ZdfSEpK4uGHHy5Wu1I5aNBP5ApHjhwBsu62CAkJybfegAEDaNq0Kdu3b2f//v388ccfREREEBERwb59+3jttdfy/ED5J09PzyLF989EKzMz0/7/f/b3zykLzGZzkfrKzz/bLSiG7DuY8it3pP38+vqnhg0b5pnwOnInzg033GCf+qIw6enpzJo1C4Bbb72V2267jUWLFrFjxw6+++47br31VofaKQn16tWjXr16DBw4EIvFwtq1a1m2bBk2m429e/dy8803c8MNNxAREUFUVBQpKSn2qSqulH1nEPw9ZcKVfwAkJyfnSqquTGKz74y60ubNm2nRogUAb775JvPmzSMhIcE+z3i2+vXrA1lJc2xsbJ7J24ULF/Dy8rInWldatmwZ3bt3z7VdRETKB+VWhVNupdwKKm9uZbVaGTdunH3A76677uKFF1646rvlRUSqOuVWhVNupdwKKm9udSU/Pz8GDx7Mzp072bdvHxs3btSgnwBa00/E7syZM3z22WdA1qLzhc1z3aJFC5555hm2b9/Ojz/+yLRp0wD45ptv7ElYSYuKisJqtdq/v3K6geyFcrOThbi4OHtZZmZmnvOKO+raa6+1Jz7Zc79nu/L7unXrXnUf2bIXaYas481mNptzfA/YH7UHGDhwIOvXr8/1deXitiVh1apVnDp1Cjc3N5555hkefvhhe8IxZ86cEktS85KSksJ7773H3Llz7XdsZXN1deWxxx7DaDQCcPnyZQD7tEmpqam8//77ebabvd3f398+X/6V5/LK5CrboUOH7P+/4YYbCox78ODB9tdo3rx5OaZi6Ny5s/3/W7ZsyXP/uXPncvvtt7Nw4cIC+xERkfJFuVX+lFv9TblVlsqaW7344ov2KT0HDx7MsmXLNOAnInKVlFvlT7nV35RbZamMudXkyZO57777WLBgQY7t2U8NXvmekqpNg34iZM2xPX78eMxmM15eXowZMybfuseOHWPgwIF07tzZ/ui5j49Pjg+B7Lt+sj/I4uLiCpxr3VFxcXH2xYQTEhL44IMPgKzpCLITiex/9+/fT0xMDJD1oZT9/ys5Gl9gYKA9Cdm6dat9juuYmBjeffddIGsx6Xr16hX3EKlduzY1atQA4IMPPrA/Pv/ee++RkJCQo+4111xDkyZNgKxFlrOnXzh48CAjR47k6aefvurH7/Pyxx9/8PrrrwPwyCOPUL9+fdzc3JgxYwaQtfjwG2+8UWL9/ZOnpyevv/46b731FvPnz881RcCHH35oT65vvPFGADp16mT///Lly/n666/t9TMzM1m7di2ffPIJABMmTLD/0XDbbbfh7+8PZN2VdOUUIj/99BP/+c9/AGjfvr39fOXH1dWVp59+GsiaimTFihX2shYtWtCpUycAVq5cye7du+1lFouFVatW8dlnn5GSklLg1CUiIlK+KLdSbuUI5VZZKmtu9euvv9rPX8+ePZk1a5ZDT1CIiEhuyq2UWzlCuVWWyppbpaenExkZybZt2+zHGxMTw48//ghAo0aNSrV/qTg0vadUSVcugJucnMzvv/+O2WzG29ubl156qcC5tK+77joyMjKIioqiW7du9l+o2XdJtWzZksaNGwPYk4mUlBR69uzJjTfeyEsvvVTkeLOnB7juuut4/vnnefvttzl37pz9Do7HHnvMXrd37958/fXXpKSkcM8991C7dm3OnDlDu3bt2LdvX447rooS34wZMxg0aBAXL16ke/fuNGjQgGPHjpGcnIy3tzdz5swp8nHlxWAwMHToUObPn8/Jkyfp2rUr11xzDdHR0TRs2DBXwjB16lSGDx/OoUOH6Ny5M3Xq1CEyMpL09HQGDx6c56P1/1TQgsgAw4cP57bbbmPGjBmYzWZq1qzJ448/bi9v27YtPXv25OOPP2b16tX07t27wGk2rpbBYGDu3LmMHDmSixcv0rt3b2644Qb8/Pw4d+6c/Y6ytm3bcs899wBZU2ssX76c4cOHc/ToUYYPH069evUIDg7m+PHjXLp0yX6MgwYNsvfl4+PD3LlzmThxIn/88QfdunWjQYMGpKSkcOLECWw2G7Vr12bevHkOxX7rrbfSpUsXdu/ezZtvvkmfPn3s75358+czcuRIfv31V0aPHm1PoE+ePGlP+vv375/nOcpvQWTIWui5KOvF/PLLL4wbNw7IWnsm27hx4+xJ5fvvv18q51ZEpKJTbkWR41NupdyqsudW69ats19UPnHiRK7+itqeiEhVotyKIsen3Eq5VWXPrSZOnMi+ffuIj4+nR48eNGzYkD///JPExERcXV154oknHG5LKjcN+kmVdOUCuO7u7oSGhtKhQweGDBlS6KLCLi4uvPHGG6xZs4Y9e/Zw5MgRDAYDtWvX5q677uKRRx6x38E6aNAgfv75Z77//nsuX76cYzHjosgegGjQoAHPPfccCxYsIDk5mdDQUB5++GH69+9vr9urVy/OnTvHxo0buXTpEu7u7rz++uu888477Nu3L8dixEWJ7/rrr2fz5s2sWrWKb775hsjISAICAujYsSOjR4/m+uuvv6pjy8vDDz9MUlISGzduJCEhAQ8PD9auXcubb76ZK3lq164dGzZsYNWqVfz2228cPnyYunXr0r9/fx566CGH+itoQWTISkg3btzIL7/8AsBTTz2Va47xqVOn8uWXX5KcnMzzzz/P8uXLi3jUjmndujWbN29m/fr1/Pjjj5w6dQqz2Yyvry+tW7emR48e9O/fP8e5rFGjBps3b2bjxo18+umnHDt2jDNnznDNNddwzz33MGjQoByLFGfr1q0b77//PuvWrWP//v0cPXoUNzc3GjduTJcuXXj44YeLtPDwU089xd69e8nIyGD27Nm88847GAwGAgICePvtt9m2bRsffvghR48e5fz58wQHB9OxY0cGDBhAx44d82wzvwWRIeeC2o7IyMiw3w14pSunR7BYLEVqU0SkqlBuRZHjU26l3Kqy51ZXrqUTERFR7PZERKoS5VYUOT7lVsqtKntuVa9ePbZs2cLq1avZv38/kZGRBAcHc+uttzJ69Gg96Sd2BltBq4+KiIiIiIiIiIiIiIiISLmnJ/1ERMrYfffdZ1/AuCBjx46lT58+pR9QJbJmzZp8F4K+UsOGDVmzZo0TIhIREZHSptyq9Ci3EhERqXqUW5Ue5VZSGvSkn4iIiIiIiIiIiIiIiEgF51LWAYiIiIiIiIiIiIiIiIhI8WjQT0RERERERERERERERKSC06CfiIiIiIiIiIiIiIiISAVXrgb9nn/+eRo1amT/ft++ffTu3ZsWLVrQtWtXPvjggxz1N2zYQMeOHQkLC6N///5ERETYy9LT05k5cya33HILN910E2PHjiU2NtZpxyIiIiIiIiIiIiIiIiLiLK5lHUC233//ne3bt9u/P3/+PKNGjWLixIn079+fffv2MX78eOrVq0dYWBi7du1i6dKlrF69mpYtW7Ju3TpGjhzJzp078fLyYtGiRRw4cIAtW7bg7e3NU089xfTp01mzZk2+MVy8mFisYwgK8iY2NrlYbUjx6TyUHzoX5YfORfmhc1E+5HUeqlf3LaNoKq/i5lYF0XupYtJ5q3h0ziomnbeKp7KeM+VXJUu5VdWmc1S+6fyUfzpH5ZvOj2Mcya3KxZN+mZmZzJo1i0ceecS+7cMPP6Ru3boMGTIET09POnXqROfOndm8eTMAmzZtol+/frRt2xZPT09Gjx4NwJ49e7BYLGzbto3x48dTp04dgoKCmDp1Kl988QXnz58vlWMwGMBodMFgKJXmxUE6D+VHZToXbt9+jefnS/HcuxS32K/LOpwiq0znoqLTuSgfdB4qPp3DiknnreKpyufM7duvcduzG7dvnZP7ucV+jVvM7hLJNavyeauodM6krOlnsPzTOSrfqsr5uZr8qCRznOKoKueootL5KVnl4km/jRs34uHhQa9evVi6dCkAkZGRNGvWLEe9pk2b8umnn9rLe/ToYS8zGAw0adKE8PBwmjZtSlJSUo7969evj6enJxEREdSoUaP0D0pEKg3fx0dgnH4GgsAaXovYDofLOiQRERERKUW+j4/AePYM1pq1iP2t9HM/3/ARGNPPYHVXrikiIiLl09XkR8pxRJyvzAf9YmJiWLVqFW+99VaO7XFxcTRu3DjHtoCAAPu6fHFxcQQEBOQo9/f3JzY2lri4OPv3V/Lz8ytwXT83N+NVjyZn72cyGbHZrq4NKT6dh/KjMp2LK38vGAxZx1SRVKZzUdHpXJQPOg8iIiIiIiIiIlIZlfmg3/z583nggQe4/vrriYqKsm835DP6lr29oPL8ygraD8BstjoScj7tZv2bkWHVBcQypPNQflSmc3Fl/DZb1jFVJJXpXFR0Ohflg86DiIiIiIiIiIhURmW6pt++ffsIDw/nsccey1UWGBhIfHx8jm1xcXEEBQUVWp5d58pym81GfHw81apVK9FjEBERERERERERERERESlrZTro98EHH3Du3Dk6dOhAmzZt6Nu3LwBt2rShUaNGRERE5Kh/8OBBwsLCAGjRogXh4eH2MqvVSmRkJGFhYdSpU4eAgIAc+x85cgSz2Uzz5s2dcGQiIiIiIiIiIiIiIiIizlOmg35PPfUUn332Gdu3b2f79u2sXbsWgO3bt3PPPfcQHR3N+vXrSU1NZceOHezdu5cBAwYAMHDgQLZs2cL3339PSkoKL730Eh4eHnTq1Amj0cgDDzzA0qVLOX36NJcuXWL+/PncddddBAcHl+Uhi4iIiIiIiIiIiIiIiJS4Ml3Tz9/fH39/f/v3FosFgJCQEABeeeUV5syZw+LFi6lVqxaLFy+mcePGAHTo0IEpU6Ywbdo0Ll26RPPmzVm7di3u7u4AjBkzhuTkZPr27YvVaqVjx47Mnj3buQcoIiIiIiIiIiIiIiIi4gRlOuj3T7Vr1+bIkSP271u1asX27dvzrT9o0CAGDRqUZ5nJZGLmzJnMnDmzxOMUERERERERERERERERKU/KdHpPERERERERERERERERESk+DfqJiIiIiIiIiIiIiIiIVHDlanpPEZHyKPa3w2UdgoiIiIg4kbPzv9gOyjdFRESkfLua/Eg5jojz6Uk/ERERERERERERERERkQpOg36VWL9+vejSpT0pKSm5yjZufJv27VvxyScflkFkzvPHH0cYNWoonTrdxn339WDjxrfzrTtv3mzuuKMNnTrdav/q3v1Oe/nly/HMmjWNbt3uoHv3jixYMIf09LQr+jrKuHGjuOuuO7j33u4sXfoiZrO5NA9PREREnEi5VfFyq44db6VVq1Y56hw+HMmAAX34978fybedzMxMhg17iCee+HdJHYaIiIiUE8qvipZfzZ1b8LUryD+/stlsvPPOW9x5Z1v++9/NpXAkIiJSHmjQr5Lz9PTiq6/25Nq+c+enBAYGlUFEzpOWlsaTT46jRYuWfPTRLubMWcj69evyfD2yDRkylD17vrN/7djxpb1s/vzniIuLY+PGrbz11nscPXqE1atX2PuaNGkMzZuH8eGHu1i5ci3ffruX//xnQ2kfpoiIiDiRcqurz62++OI7fvrpJ3vZzp2fMn36ZGrXvrbAfrdufZ+oqFMldhwiIiJSvii/KrlrVwXlV1OmjOfAgf34+vqVxqGIiEg5oUG/Sq5du9vYsePjHNtOnDhOQkICdevWy7H9v//dwoMP9qNr1w4MHfog33//HQDr17/G0KH/ylH3t99+oVOn20hOTiIjI4OXXlpIz56dufvuTkyaNJbo6CgALBYL7du34quv9vDYY0Pp0qU9jzwymGPH/gRg//4fuOuuO/jhh30MHHgfXbvezuTJ40hOTrL3tXXrJvr3703XrrczbNhD7N//vb1s/frX8r3r+7vvvsFiMTNy5BN4eXnRvHkL7r23L9u3by3y6xgbe4lvv/2aMWMmEBRUjerVr+Hf/36cjz/+ELPZzKVLMbRteyuPPjoCk8lEnTrXcuednfn11wNF7kvKH69F8/F/tTMB/+mM17H5ZR2OiIiUIeVWJZNbAWRkpLN27XqaNm2Wb52YmBg2bHidfv0GXlUfIlfLa9F8vGdMw2uRc3I/r2Pz8T4yTbmmiFRJyq+ck181a9aCRYuW4e7uflVti1xNfqQcR8T5NOhXyd12WwcOHTrIhQvn7ds+++wTOnbskqPeN9/sZc2aFUyZ8jSffPI5gwY9xNSpE/jrr2N063Y3f/xxhJMnT9jrf/nlHm677Xa8vX14441X+euvY2zYsJH//vcT6tevz1NPTSQzMxNXV1cA3n33bZ555lk+/ng3Pj4+vPbaagCMRiNpaWl8/vlOXnvtLd5+exORkeF8/PEHAOzf/z3r17/GnDkL+fTTLxgy5FGeemoS58+fA+CRR4azcuXaPI/96NHDNGjQEKPRaN/WsGFjDh/+Pd/X68CBn3j44YF0734no0YN4/DhSCBr6k6j0Uj9+jfY6zZq1JjU1BROnTpJaGhtpk+fZT9egPPnz1X6O9KqCo+3N2Dy24/bNfvxiNbTmyIiVZlyq+LlVocOHbKX3XNPH4KDqxf4ei9fvpi+ffsTGlq7wHoiJc3j7Q14vbIKj7edk/t5RG/A69Qq5ZoiUiUpvyqZa1dQcH71yCPDMRgM+bYrUpiryY+U44g4nwb9isFz9UqCWjYmqGVjAsMaQ+3aBIY1tm/L/vJ7aECuff0eGpCrXl5fnqtXFitGX19f2ra9lc8++xTImr979+7P6Nate456H3+8nc6du9Gy5U24ubnRtWt36te/gS++2E2tWqGEhd3Izp2f2uvv3fuFvY3t27fy8MNDCQ6ujru7ByNGPE50dDRHjvydoHTrdje1a9fB3d2DDh3u5NSpk/Yyq9XKoEEP4ePjQ40aIYSF3Wgv37ZtCz179qZx4ya4urpyxx2daN48jM8/31nosV++HJ9rygI/Pz8SEi6TmZmZq35oaG3q1LmWhQuXsGXLRzRt2pwJE54gPj6ey5fj8fHxwcXl77dMdtvx8XG52vrmm6/45puvGDz4oULjFBERkSxX5lYFffn+S7lVRc2thg0bRnx8fKF9Afzwwz7+/PMoDz74sEP1RUREJDdH8qvAsMbQu3eufZVfVYz8KvvalYiICIBr4VUkP4bEBIxnz+TYZsyjXmat0FzbXGJicu2bXx/F1b17T9aufZmHHnqEgwd/xd3dgxtuaJSjzpkzZwgLuynHtlq1Qjn7vxi7d+/JW2+9wYgRo/j99whSUlJo2/Y2EhISSEi4zJQpE3LcLWS1Wjl//hxNmmRNJ1CzZk17mclkIj09PUdfNWvWyrM8OjqKb7/dy3vv/cdenpmZyXXXXe/AkRft7qVHHhme4/vHHx/L7t2fsXfvF3h4eObfyz/ukvrqqz3MnTubGTOey/U6S8WXmZnJ8eN/FVrP19eP4ODgAuvExMSQWMh73JF2CmvLYIDLl30wm12oVq3wtkREykpeuVVeMkOVW1XU3Orzz3eyd+8X9Op1X4H7pqens2TJC0yePB2TyVSkfkXEuUoypxWRkudofsXF3GvAKb8qf/nVo48Ox2b7+/srr1317l1wfiVS1VyZo2RfG4uNTcrxHlKOIpWRBv2Kwebrh/WKD3yjiwFrpi1Xvcw8fnFkBgfn2LegPoqrXbvbWLBgDkeOHGbnzk9z3SlVkOxkqGPHLixZsojw8IN8881eOnbsjJubmz3BWb16HY0bNy2gnYIfKs1vegEXFwMjRz5xVU/MBQQEEB19Ose2y5fjCQgIyPHEXn6MRiPXXFOD2NhLNGvWnMTERKxWq33KhcuX4//XT6B9n+3bt7J69Qqef34RrVu3KXLMUv7Fx8czacnkQut5+3iwZNmyfBOHmJgYJowbR3JSWrHacbQtV1cj7h5uhbYlIlKW/plb5SczjxsYlFvl3c8/lXVuVbNmTS5dulRo3TfffJ1mzVpw882tixyniDhPSea0IlI6HM2vjNVzTwmp/Crvfv6prPOr7GtXIvK3vHIUV1cjFos1Rz3lKFIZadCvGFJHPUHqqCeArLsFgoN9iYtJzHG3QH4S3nqvlKP7m5ubG506dWXPnl189dUXvPpq7jmUQ0Nrc/r0yRzboqJOc+ednQDw8fHh9ts78OWXe/j227089dQM+3Z/f3+OHfszR+J09uyZHHdAXa3Q0Nr89defObadO3eOGjVqFDoPeZMmzdi+fSsWi8U+P/vvv0fY7+C6ks1mY+XKJfTseS/XX18fyFrI+ezZaGrVCqVhw8bYbDaOHfuDhg0b29vy8fHh2mvrAvDFF7t59dXVrFixRk/4VWI2m42urYcRHJj/z3dM3Bl27V9HYmJCvklDYmICyUlpBbblSDuOtnU56TyffLe20LZERMrSlblVQQwGcP/HNuVWjinr3Or06dP06ZP7Sc1/2rnzUxISLtOzZ2cAMjLMZGSk07NnZ15//T/UqBHi0PGKSOkqyZxWREqHI/lV9jUtYhJzbFd+5Rhn5lfLl7+U77UrEflbXjmKm5sRs/nvQb/ymqM4MosC6ClFyZ/W9KsiunfvyfbtW6lT59o8E5peve7l8893cvDgr2RkZPDxxx9w8uRxOnfulqONjz76LxkZGYSF3Wjf3rt3X9566w1OnjyBxWLhvff+w4gRQ0hLK/huT0fce29f9uzZzb5932K1Wjlw4CeGDBmQY5Hi/LRteyteXl6sWbOSlJQUfvnlZz744L/07fsAABcvXmDw4Ps5cyYag8HA+fPnWLp0EZcuxZCSksLLLy/Dzc3E7bffib9/AB07dmH58peIjb3EuXNneeWVVfTu3RdXV1eSkpJYvHgBs2fP04BfFRAcWIuQ6nXz/SpoQLAobRWlnZJuS0RECqbcqui51apVyzCZTHTocGehfa1Z8zpvvfU+b7zxDm+88Q7Dh4+kceOmvPHGOwQH534SQUTKlvJQESkJyq+Kd+1KRHK7MkepeU29cp+jZD+hOGn85EK/JowbR0xMTFmHLOWQnvSrIpo3b0FAQCDdut2dZ3m7du159NERzJ79NImJCdSrdx0vvbSSOnX+ntP9llvaYTK507Vr9xx3Kj3yyHCSkpJ4/PFhpKenc8MNDXnxxeV4eHgUO+7WrdsyevRYXnppIZcuxRASUpNJk6ba73hav/41fvrpR1auXJtrX5PJxAsvLGXRoue5556uBAYGMnr0WNq1uw3Iuhvq1KmTmM1mAKZOncHy5Yt5+OFBWK1WmjRpxrJlL+PpmbWe3+TJ03nxxfkMGHAfrq6udOvWnREjRgHwzTdfER8fz5Qp43PFsWfPd8V+HURERKR8UW5V9NyqadNmrF+/Hk9PT2w2GDSoL+fPn8NqtZKZmUmnTrcC8M47WwgJqZmjb19fP9zc3LjmmhrFfg1ERESkfFJ+VXh+9dRTM1i2LP9rV/nlV4sXr2DSpDEAZGRksGTJIpYvf4mWLW9iyZJVxX4NRKRkODKLApTfpxSlfDDYbI5MRlk1XLyYWHilfGRPhRDj4PSeFVFychL3338Pa9dusE9pWd5UhfNQUZS3c+HIo/H5PRYf1LIxxulnIAguJLmz+cwuQqrn/x44d/Ek7+6cw+Kli/JduPv48b+YNH4yg7rNyLetcxdP8ubHM5gy7Ulq166Tb39RUadZtOAlHurxbL5tXYqP4s2PZxcYk5S+8va+qKryOw/Vq/uWXVCVVHFyq4JUlvdSRcitSlJlOW9VSVU+Z0EtG2M8ewZrzVrE/na49Pvb2xhj+hms7rWI7VC8/px53hzNaQvLjau6yvxeU35VspRbFa6y5leV6RxVRlXl/FxNflSSOU5R5JWjmEyuZGRY7HXKY47iSG4F5TP24qgq76GS4EhupSf9xCHp6em89NIL3Hxz60qVNEnVkNfivXkpb4v3JibHc/LkCRbOexGTuynfeqlpKVw4dxGzOaPA9szmDKKiThdYR/OBi4g4h3IrERERkZKl/EpERESDfuKAgwd/ZcKE0TRp0ow5cxaWdTgiRebIo/EFPRZvbncbxO7Fmmbl10RXKHgd7hKTlp6Mi8GNLq2HEhpyXb71jh4/wKbolVis1nzrJCbHOTSAWN4GPkVEKiPlViLln7ndbVhjL5EZVM05/QXehtV8iUw35/QnIlLZKL8SKX1Xkx8pxxFxPg36SaHCwm7k88+/LeswRIote/Heokpcsw7IesR+zvjJDOpWyA4lLCggpMC4L8ZGF9pGalrhA4iaD1xExDmUW4mUf9n5n9P6a+Hc/kREKhvlVyKl72ryo6qU4xRnaSGRkqRBPxEpt/RhWfIKG0AUERERERERERERx1XUpYWkctKgn4iUSxX9w7Kw9fOiok5jsVjyLS8rjqz7BxpsFREREakKCrsJr7zmtCIiIiLOVNylhURKkgb9RKREZV8YMBjg8mUfYmOTsNly1nFkwKgsPixLaqAuMTm+0PXzUtNSuHDuImZzxlXHW9IciTtbeR1sFREREZGS4chNeOUxpxUREREpSY7MRJZ9zfBqlxYSKUka9BOREvPPCwOurkYsFmuuem4mA1OnTSMwMDDftpz9YVnQgNfSiJ9oOvYyLfyhxj3u/JRe8EWNtPTC1887evwAm6JXYrHmfn3KiiNxg+5MEhERkcrPv+89uFy8QGb1a7i89aPS7++ne3DJuECm6Routyr9/hzhyE145TGnFRERkdJxNflRecxxisLRmch0I5SUJxr0E5ES888LA25uRszmnBcATkYf5s3t85g5fXaBT5M5+8OyoAGvRuH341kjE4Lg+vgMvj/l2EWNgtbPuxgbXeyYS4vW/RMREZGqznjsT4xnz2BNKPiu7hLrL+VPjOlnsFqc019RFHQTXnnOaUVERKRkXU1+VJ5zHEc4chMU6EYoKV806CciJS77woDJ5EpGRs7pMC/GRjv0NFlZfVjmNeBlNBqdGkNF4Mjaf1r3T0RERERA60aLiIhIxVbYTGS6EUrKEw36SS6ffPIha9e+zIoVr1CnzrV51jl58gQPPtiPTZs+wGAwMHjw/axf/y7XXqungyqzwuawdnTNOyj8aTJ9WJZfjq79p3X/RESyKLcSkapM60aLSGlQfiUiIpI3DfpVYv369SI+Po4PPtiJl5dXjrKNG99m5cqlTJ8+ix49etm3nzt3lq1bN7FmzeuEhNR0qJ+QkJrs2fNdicZ+tc6ePcPUqS/w008/4eHhSY8evXjssSdwcXHJVXfdulfYsGEdrq453wabN39IUFA10tPTWb58MXv27MZisdCmTVuefHI6AQEB9rrr17/Gtm2bSElJoWnTFkyd+jS1aoWW9mGWCUfmsC6L+asduWu4KIORUjhH1v7Tun8ipevrr79m6tSptGnThiVLluRZJzk5mZ49e9K2bVsWLFgAQGZmJsuWLWPz5s0kJSVx0003MWfOHOrUqQNAXFwczz33HF999RVGo5Fu3boxY8YMPDw8APj999959tlniYyMJCAggEcffZRHH33UOQddDlTV3GrRovkcPPhLsXMrgM8//5wFCxZy7tw56tSpwxNPjKd167b2ulUptxKpKrRutIgURPlV8fKrhITLLF/+Et9//x1mcwbXX9+A0aPH07x5CwDat2+Fm5sbBoPBvm+vXn2YMGFK6R6kiIiUGQ36VXKenl589dUe7r77nhzbd+78lMDAoFz1bTYbixcvx98/wEkRlhybzca0aU/SuHEjtm37hNjYWCZNGkNQUBADB/4rz33uuqsHTz89O8+y1atXcPDgr6xb9xZeXt7MmzeL+fOfZeHCrIur27Zt5ttv9/LKK+vx8vJm5colbNz4NhMnTi2tQyxTjsxh7ewpOR29a1iL6ZYOrf0nUjZeffVVNm/eTN26Bb//VqxYQWJiYo5tb775Jlu2bGHdunXUrl2bhQsXMnr0aLZv347BYGD69OkkJyezc+dOrFYro0aN4sUXX+SZZ54hNTWVESNG0Lt3b9atW8cff/zBiBEjCA0NpVu3bqV5yOVKVcutpk9/kuuuq8/WrZ8QF1e83OqPP44ya9Ysnn12Po0aNWb79m289tor3HRTK1xdXatcbiVS1Sh3FJH8KL8qPL965pnZBAf7EhOTiM32d9nzzz8LwH/+swkPD0/Wrl3F1Knj2b79M/tA4TvvbKFmzfzXIhMRkcol9y0kUqm0a3cbO3Z8nGPbiRPHSUhIoG7dejm2b926ibFjH6Nfv14MG/YQ+/d/by/LSkLG0rVrB/71rweIjAy3l509e4b27Vtx8uQJAKKjo5g4cQzdu99Jjx6dmTVruv2iY1TUadq3b8VPP/3Iww8PpEuX9jz++HAuXDhvb+/LLz/nwQf70bnzbTz00APs3PmpvWzHjo/p1+/vu7uudPhwJMeO/ckzzzyDn58fdevW41//epjt27cW+XWzWCx8+umHjBjxOLVqhRIQEMATT0zg22+/JibmIgDvvPMW48dPISSkJn5+fkyfPqtKXJTKnsM6r69A/xpOjeXKu4YHdZuR71f7Fv2xWjO1mK6TZT+Fefz4X/l+xcTElHWYIhWOu7t7oYN+hw8f5qOPPqJv3745tm/atInhw4fTuHFjfHx8mDp1Kn/99Re//vorMTExfPHFF0ybNo3g4GBq1KjB+PHj2bJlCxkZGXz55ZeYzWYmTZqEt7c3N954IwMGDOC9994r7UMuV6pibjV+/JPFzq0ANm16lyFDhtCy5Y24u3vwwAODeOWVN664IFU1cysREZGqTvnV1edXnTp1Zfz4Kfj7B+Du7k7Pnr25fPkycXGxV9WeiIhUfHrSr5K77bYOPPvsM1y4cJ5rrskakPnss0/o2LELv/8eYa+3f//3rF//Gi+8sJQGDW5g794vmTp1Eu++u4UaNUJYtmwx6elpbNnyEWlpqTz77DP59rlw4VwCA4PYvn0HaWlpTJjwBOvXv8aYMRMwGo1A1kWfl15aicnkzr///TDvvvs248ZN4uTJE8yb9yzz57/ITTfdTHj4QZ58ciyhoXVo1qw53bv3pHv3nnn2e+TIYUJCahIQEEBMTFai1rBhY06fPkVKSjJeXt659jl27A9GjHiYU6dOEBpam8ceG8Mtt7TlzJkokpOTadSosb1u3br18PDw4PDh32nUyMaFC+eIjj7NnDkzSEhIoFWrW5g0aWqFvNOsotP6gOWP1v0TKT1DhgwpsNxmszF79myefPJJTp8+bb94kZ6ezrFjx2jevLm9ro+PD9deey3h4eEkJSXh6upKo0aN7OXNmjUjJSWF48ePExkZSePGje2f5QBNmzZl06ZNJXyE5VtVzK38/Pzt2642twL47bdfuemmlowY8QgnTx7n+usbMHHiVG64oSEXL15QbiUiDk3d7+vrp9xRpJJRfuVofnWSWrVCc+RX3brdba8XFxfHxo3/ISzsRoKDq9u3r1mzgl9//QWwceutHRgzZkKuqVRFRKTy0KBfMXieXInnyZV/b3AxEJhpy1XP4tuShJty3gXv98sAXBN/K7SP1LpPkFr3iauO0dfXl7Ztb+Wzzz7loYcewWazsXv3Zzz//KIcidO2bVvo2bM3jRs3AaBTpy5s3fo+n3++k8GDh/D1118ya9Y8/Pz88PPzo2/fB/jtt1/y7HPRoqUAuLt74O7uQZs27Th0KOex9ulzP9WqZf2h1rbtbZw6dRKADz7YSvv2HWjV6hYAWra8iU6durJjx8c0a9acgly+HJ8jaQLs38fFxeVKnK65pga1atVm+PDHqFEjhA8+2MqUKePZsGEjly/H59j/79fTj/j4OC5cuIDBYGDv3i955ZU3SEtL45lnprJw4Tyef35RgXGKVAVa90+k7Lz33nu4ubnRp08fVqxYYd8eHx+PzWbD3z/nZ5u/vz+xsbH4+/vj4+OTYy2R7LqxsbHExcXl2jcgIID4+HgyMzPzXIOkqHLlVvmw+LWErp/k2KbcqnznVnXr1uPChQts3ryZGTPmEBxcnVWrljFlyng2btyq3ErEyWJiYkhMTCiwjrPXxdZNYyKlw9H8iuCbodl/cmxSflV+8qsRIx6jadMGvP76mznyq2wDB/YlKuoUN974f8ydu9C+hl+zZi24+eZbmDr1GS5evMjMmU+xePF8ZsyYU2CcIiJScWnQrxgMlgSM6WdybDPmUS/TIzTXNhdzTK598+ujuLp378natS/z0EOPcPDgr7i7e3DDDY1y1ImOjuLbb/fy3nt/J3iZmZk0aHADly/Hk56eTkhIiL2sdu06+fZ36NBBXn11NSdPHicjIwOr1UqjRk1y1AkJ+XsucZPJRHp6mj2Offu+5auv9uSIo02bdoUe55WLEjtS1qtXH3r16mP/fsCAB9m9+zN27PiYW29tX2BbFosFi8XCqFFj8PcPwN8fhg9/jCefHEt6ejru7u6FxussjvxBr7tlpbRo7RYR57p06RIrVqzgzTffLNJ+BoOh0M/Rgsrz4+ZmpCi7udqSHMqPbObaAJhMRvuaJkbLJYf2dbUlYTLllbEVzmDIOqZ77unF6tUrGTZsGL/8cgAPDw+aNWuKi4sBV1cXTCYjZ85E8e23X+fKrRo2bEhKSiLp6enUqRNqj+W667J+V7q5/R2bm1tWW7/+Gs6aNas4ceLv3KpJk6aYTEZ7/Tp1atvb8vR0x2xOx2QycvZsNN9++02u3Kpdu1sLfR1cXbPO35X13NyyBndNJtdc+99///3cf//99u8femgIn3++k127PuXxx5/AarXw0EMP0bBhA2w2mDRpMp06fUh4+G94enpisVgYN2481atXA+Cxxx5n/PgnsNks5Sq3qkqy379Xvteqiuxj/+d7oCL0V9h5i4m5yMQJ40lJTCuwndS0FM6dvYDZasbgkvcvc4NLVn8Gg6FYdQDSzckYXdzocstQatfM76axs+z+cR3p6cmYTM5dWqA0VeX3mpS+vK5d5Snt2lybdO2q/Fy7MhjAy8uLgQP/vnY1cuRoe72NG7cSFxfHhg3rePzxEbzxxn/w9PTklVfesNepW9ebxx57gqlTJzJ16gxMpvxvsBARkYpLg37FYHP1w+r+dwJgdDFgzeNJv0y33IMpmW7BOfYtqI/iatfuNhYsmMORI4fZufNTunXrnquOi4uBkSOfYPDgh3KVZa9hd6XMzLzXRktOTuLppydz7719Wbr0ZTw9PXnttTX8+OP3Oerl9zSAweDCvff2var1WwICAklIuJxjW3x8vL3METVrhhIbe8le//Lly3h6egJZ06VdvnyZwMAg/PyyzouPj88V+9bEZrMRFxeXI8ksSzExMUwYN47kpIL/oNfdsgX7vfs4rjn+NZePXmLDqb+o0bjwfUREysKCBQt44IEHqF+/fq6ywMBAXFxc7J+N2eLi4qhWrRpBQUEkJiZitVrtUxrFxcUB2MtPnjyZa9/sdvNiNhdtLVWjwceh/MjqVg1XICPDar846uFaDYMD+1oMPmRkXN0arzZb1jG1bt2OuXOf5dChCD755GO6du1ORoaVzEwbFksmGRlWDAYDI0eOLjC3Mput9ljS0832bdnM5kzi4i4zdeok7r23L0uW5MytMjKs9vpWK/a2rFYbmZm2/70+hnxzq8JeB19ff+LjL+eod/Fi1vow3t5+Dr2OISG1uHjxIhkZVnx9/fD19bWfN6PRRECAPxcuXKRx46YAmEye9narV6+BzWbj/PmYcpNbVTXZ1x6vfK9VFckTp2JITsbm7X3VvzOK1N91UzFYk7EZi99fYeft0qV4khJS6dp6GMGB+f/ePHr8AJuiVmIxW7Dl8XcugC0z63ejzWYrVp0r6wX5h1CjWt43jdkyIdOW9fvNGefFWarye01K3z+vXeXH6FE91zZduyqda1eXL5fMtat/CgwMZOzYiXzyyYd8//23dOzYJc99MzMziYuLpUYN5VdSNCmT/s6PHN7n+qwcJzHVxunjfxVaXw8miBSfBv2K4crpCwwGCA72JS4m0aEk/Z/TfZYmNzc3OnXqyp49u/jqqy949dUNueqEhtbmr7/+zLHt3Llz1KhRg4CAQFxdXblw4TwNG2aNdpw+fSrPvk6dOklycjIPPTTUPlj2559HHY41NLQ2hw9H5th24cJ5qlULzrGGUF6aNGnKuXNn/3eBMutH+/ffI6hX7/o85yrfsGEdYWE3ctNNN+eIv2PHztSqFYqfnz9Hjvxuv8h07NifWCxmGjdugp+fP97e3hw5ctg+j/rZs2cxGo3l6oMpMTGB5KS0Av+g1xSLhTvRfjAnGMyhI9/xn30zmKhBvxLjyLotWfXMuLm5FVhHiaEIfPDBB/j5+fHOO+8AkJaWRmZmJl988QU//PADDRs2JCIigtatWwNZFxhOnTpFixYtqFOnDpmZmRw5coSmTbMGYA4ePIivry/16tWjRYsWbNy4EYvFgqurq708LCysxOJ3dGoogwH++dyXcqu8FTe3On/+LJcvx9vX1bva3AqgceMmREREcPPNtwKQkpJCfHw8ISE1qVPn2gqRW0nVkTbkUef2V9u5/QEEB9bSutgiVYAj+VX2NS1iEnNsV36Vt7LIr/7v/3LnV6mpqTz00APMnbvQfgMVZA12urgY+eOPI+zatYPHHx+XY1+TyUT16tc4fLwi2a4mP0qr/WjWQwnTx5Gc9GWh9fVggkjxFX/xFakQunfvyfbtW6lT51pq1sw9+HPvvX3Zs2c3+/Z9i9Vq5cCBnxgyZABHjx7B1dWVm2++hU2b3iMpKYlz587x3/9uybOf4ODquLi48MsvP2OxWHj77fXExMQQFxfr0HoQvXr14dCh3/j004+wWCz88ccR/v3vR/jqqy8K3feGGxrRpEkz5s6dS2JiIseO/cnbb6/n/vsfsNcZPPh+fvvtVwASExNZsuQFoqOjSE9P59133yY6+jQ9evTCaDTSu/d9vPrqas6ciSYuLpYVK17izjs7ExRUDVdXV+65pw+rVy/nwoXzXLoUwxtvvEr37j3tF0LLk+w/6PP6KujuXpHSdOW6LZPGT873a+zocQzo9wDjnphQYL0J48YRExNT1oclUqa++uorPvzwQ7Zv38727dsZOHAgnTp1Yvv27QAMGjSI1157jcOHD5OYmMjcuXNp3rw5YWFhBAYGcvfddzN//nxiYmKIjo5myZIlDBgwADc3Nzp06IC3tzeLFy8mOTmZH3/8kffff58HH3ywjI+6bFSl3GrJkkXFzq0A7ruvH++++y4HD/5KWloaa9asoFatUFq0aFnhcisREREpecqvsjiaX3l6elKv3nWsXr2CS5diSE9PZ926V3BzM9Gy5U0EBlZj27YtvPfef7BYLJw6dZJXX32ZPn3uL5H1uEUcdeVDCYO6zcj3q2vrYSQnpRW6TJGIFEx/QVcRzZu3ICAgkG7d7s6zvHXrtowePZaXXlrIpUsxhITU5Mknp9GoUdbdUdOmzWDOnFncd9/d1KgRwogRozh48Nccd/sDVK9+DSNHjmbBgjm4uBi49977mTnzOcaMGcmYMSOZObPghYLr1q3HrFnzWLduDYsWPU9QUDUGDnyQTp2ypiTYseNjXnttDZs3f5jn/nPnLmDp0he4997ueHl5c999/bjvvn728lOnTpKamgLAyJGjycy08vjjw0lLS6V+/RtYunS1/W6nYcNGkpKSzNCh/yIzM5PbbrudSZOesrf12GNPsGLFSzz88CCMRhduu60D48ZNKuxUiMj/pKUn42Jwo0vroYSG5L1uC/xvaqlTK+n0f4/kW09PrEpV0qJFCwD7BYndu3cDcOjQoVxTIPr4+ODp6WnfPnDgQC5evMjQoUNJTk6mTZs2LF++3F7/2WefZfbs2XTt2hU3Nzd69erFuHFZdwabTCZeeeUVZs6cSbt27ahWrRpTpkzhjjvuKPVjLo+qSm41Z84CFi16nj59ip9btW/fgQkTJjB79jMkJibSpEkzFi1aZj9e5VYiIiJVm/KrLHnlV6NGDSc9PY3rr2+QI7965pnnWLlyCY88MpiMjHTq17+BRYuWERAQAMCiRUtZvXoFr732Cv7+/nTu3I1hw0Y6cDZESl5hswyISMnQoF8l9s/kYuPGrTm+X7lybY7v779/APffPyDPtoKDq7Ns2cs5tn3zzU95/v/BBx/mwQcfzlF3+/bP8qwLMGrUmBzfd+rUxZ4o/VP37j3p3r1nnmUA11xTg7Vr1xKTzzSrV/bt5ubG2LGTGDs274tJbm5uTJw4Nd852gsrl8rD4/J5PAwXCLH8xTV+hd/1J0UTFBDi0NRShdUTqSoOHTrkcN0xY8bkuS2v7QC+vr4sXrw43/ZuuOEG3n33XYf7r2yqam61aNGyfMuLklsBDB48mG7deuWZpym3kvLE5fy5rMUyjUYynbDmkUv6ObBZwWAk011rLIlI1aH8Kre88qtx4yYRHOyb63pXQEAAzzzzbL5t3Xjj//HKK2/kWy5SFFeTH7mkn8PNcp5qXumlHJ2IZNOgn4hIITou6o3nnHN0ag+9mxt5J+9lAURERESkkgjodifGs2ew1qxF7G+HS7+/H+7EmH4Gq3stYjuUfn8iIiIiRXU1+VHAD3dSLf0Max9wZ/OZUg5QRAAN+omIiIiIiIiIiIiISBVjNmcQFXU63/KoqNMOrfUpUp5o0E9ECv2AA33IiYiIiIiIiIiISOWQmBzPyZMnWDjvRUzupjzrpKalcOHcRczmDCdHJ3L1ynzQ7/DhwyxYsIDw8HBcXV1p06YNTz/9NMePH2fIkCGYTDnfcC+88AJ33521oO+GDRtYv349ly5dolGjRsyePZtmzZoBkJ6ezrx589ixYwdms5nbb7+d2bNnExQU5PRjFCnPHPmAA33ISfnnyOA1gK+vH8HBwU6ISEREREREREREyqO09GRcDG50aT2U0JDr8qxz9PgBNkWvxGK1Ojk6katXpoN+GRkZDB06lAcffJC1a9eSlJTEuHHjmD17Ng8//DChoaHs2bMnz3137drF0qVLWb16NS1btmTdunWMHDmSnTt34uXlxaJFizhw4ABbtmzB29ubp556iunTp7NmzRonH6VI+ebIBxzoQ07KN0cHrwG8fTxYsmyZBv5ERERERERERKq4oIAQQqrXzbPsYmy0k6MRKb4yHfRLTU1lwoQJ3Hfffbi6uhIUFMRdd93Fm2++Wei+mzZtol+/frRt2xaA0aNHs3HjRvbs2UP37t3Ztm0bCxcupE6dOgBMnTqVHj16cP78eWrUqFGqxyVSERX0AQf6kJPyzdHB65i4M+zav47ExAQN+omIiIiIiIiIiEilUqaDfv7+/vTv3x8Am83G8ePH2bp1q336zuTkZEaNGsXPP/+Mv78/gwYN4tFHH8VgMBAZGUmPHj3sbRkMBpo0aUJ4eDhNmzYlKSnJPtUnQP369fH09CQiIkKDfiIilVRhg9ciIiIiIiIiIlJxxcTEkJiYUGCdqKjTWCwWJ0UkUr6U+Zp+ANHR0XTr1g2r1cqAAQMYN24cv//+Ow0bNmTIkCEsWbKEn376iXHjxuHr60v//v2Ji4sjICAgRzv+/v7ExsYSFxdn//5Kfn5+xMbGOuuwREpdYR9y+oATERERERERERGRyiAmJoYJ48aRnJRWYL3UtBQunLuI2ZzhpMhEyo9yMegXGhpKeHg4J0+eZMaMGUyePJnFixfz1ltv2eu0b9+eAQMGsGXLFvr374/BYMizLYPBkG9Zdnl+3NyMFFBcoOz9TCYjNtvVtSHFV5XOQ0zMRSZOGE9KYv4fcqlpKZw7ewGz1YzBJZ/3jEvW62YwGPKt42i9K+u4/K+Oi4sBWxHbuZr+nNUWOK+/kjq+7C3l7fUsq58FF4MBk8mIyWTMt15pqUq/o8oznQcRERERERGRiicxMYHkpDS6th5GcGCtfOsdPX6ATdErsVitToxOpHwoF4N+kHWhtl69ekyZMoV+/frx9NNPExQUlKNO7dq12blzJwCBgYHEx8fnKI+Li6Nhw4b2/eLj4/Hy8gKypg+Nj4+nWrVq+cZgNl/9L4HsC4gZGVZdQCxDVek8XLoUT1JCaoEfckePH2BT1EosZgu2zLxfEFsm2GxZ75H86jha78o6mf+rk/mPuqXVn7PaAuf1V1LHl72lvL2eZfWzkGmzkZFhJSPD+YlfVfodVZ7pPIiIiIiIiIhUXMGBtQpc3uVibLQToxEpX8p00O/HH39k+vTp7NixA1fXrFAyMzMB+OGHH0hISGDAgAH2+sePH6dOnToAtGjRgvDwcPr06QOA1WolMjKSfv36UadOHQICAoiIiKBWrazBkCNHjmA2m2nevLkTj1Ck9BX0IacPuJLx9Zh38I49wcmI31nz9Xvce09ZRyQiIiIipenylg/BYgFX5/zJfPnmD8FmAUO5uS9XREREJIeryY8u3/wh0aePM3/+S7S/pRSDq4LM5gyiok4XWMfX14/g4GAnRSTlRZn+RdG0aVNSU1NZvHgxY8eOJTU1lRUrVtCqVSs8PDyYPn06devWpVWrVvzwww9s3ryZRYsWATBw4EDGjRtHly5dCAsLY9WqVXh4eNCpUyeMRiMPPPAAS5cupXHjxnh5eTF//nzuuusu/ZCLSJEl1ahPEvX5I8aTYxe3lXU4IiIiIlLKrA1ucG5/3s7tT0RERKSoriY/snrfQKq7kdPx3qUQUdWVmBzPyZMnWDjvRUzupnzreft4sGTZMo2JVDFlOujn4+PDa6+9xsKFC7n99ttxdXWlTZs2zJs3jxo1avDUU08xa9Yszp8/T+3atZk5cyZdunQBoEOHDkyZMoVp06Zx6dIlmjdvztq1a3F3dwdgzJgxJCcn07dvX6xWKx07dmT27NlleLQiIiIiIiIiIiIiIlIVFfZ0XlTUaSwWS6HtpKUn42Jwo0vroYSGXJdnnZi4M+zav47ExAQN+lUxZT53SJMmTVi/fn2eZQMGDMgxvec/DRo0iEGDBuVZZjKZmDlzJjNnziyJMEVEpJLQ9AciIiIiIiIiIuJMjjydl5qWwoVzFzGbMxxqMyggpMC1DaVqKvNBPxGR8q72/v9Svfo+6mae58L/JZZ1OFIMmv5AREREHOG+5X0MqanYPD1Jv/+B0u/v7PsYrKnYjJ6k1yz9/kSkaCIiIli4cCGRkZGYTCbat2/PtGnTCAwMZN++fcyfP5/jx48TEhLCmDFj6N27t33fDRs2sH79ei5dukSjRo2YPXs2zZo1AyA9PZ158+axY8cOzGYzt99+O7NnzyYoKKisDlVEJF9Xkx+5n32f6pdP0aXh2VKOrvxz5Om8o8cPsCl6JRar1cnRSWWiQT8RkUK02D4fzznnuC4IajU18s6pso5IrpamPxARERFHeD83E+PZM1hr1nLKoJ/3HzMxpp/B6l5Lg34i5YzVauXf//43/fr147XXXiMlJYWJEycye/Zspk+fzqhRo5g4cSL9+/dn3759jB8/nnr16hEWFsauXbtYunQpq1evpmXLlqxbt46RI0eyc+dOvLy8WLRoEQcOHGDLli14e3vz1FNPMX36dNasWVPWhy0iksvV5Efef8zEL/0Mo251Z/OZUg6wgijo6byLsdFOjkYqI5eyDkBERMTZshOsvL6CA2uVdXgiIiIiIlJOXLx4kZiYGHr16oXJZCIgIIDOnTsTGRnJhx9+SN26dRkyZAienp506tSJzp07s3nzZgA2bdpEv379aNu2LZ6enowePRqAPXv2YLFY2LZtG+PHj6dOnToEBQUxdepUvvjiC86fP1+WhywiIiIVmAb9RERERERERERE8lCjRg2aNm3K+++/T2pqKrGxsezatYs777yTyMhI+1Sd2Zo2bUp4eDhArnKDwUCTJk0IDw/n1KlTJCUl5SivX78+np6eREREOOfgREREpNLR9J4iIiIiIiIilURMTAyXL18gNjYJmy13eVTUaSwWi/MDE6mgDAYDy5cv55FHHmHDhg0AtGnThokTJ/L444/TuHHjHPUDAgKIjY0FIC4ujoCAgBzl/v7+xMbGEhcXZ//+Sn5+fvb9RURERIpKg34iIiIiIiIilUBMTAwTxo0jPc2MxWLNs05qWgoXzl3EbM5wcnQiFVNGRgYjR46kR48ePPbYY6SmpjJz5kwmT56MwWDIc5/s7QWV51dW0H5ubkYK2O2qZbdpMhnzvFlAyp7OUflWVc5P9nEaDFnHWpR9AAwuYHAp4HefC7gYDJhMxnzbN5mMuBgMDrVlMPzv962LgeyaLi4GbPnUcaQdR/srzTpFaauw17O8qCrvIWfRoJ+IiIiIiIhIJZCYmEByUho9bv03/j418qxz9PgBNkWvxGLNe1BQRHL67rvviIqKYvz48RiNRry9vRkzZgx9+vThjjvuID4+Pkf9uLg4goKCAAgMDMyzvGHDhvY68fHxeHl5AWCz2YiPj6datWp5xmI2l877Nvtia0aGVRdbyymdo/Ktqpyf7GOz2bKOtSj7ANgywZaZ/wtky4RMm42MDGu+7WdkWMm02Rxqy2bL+r1qy7TZB/oyr9jnn3UcacfR/kqzTlHaKuz1LC+qynvIWbSmn4iIiIiIiEglEhxYi5DqdfP8CvTPezBQRPJms9nIzMzMsc1sNgPQrl27XOvvHTx4kLCwMABatGhhX98PwGq1EhkZSVhYGHXq1CEgICDH/keOHMFsNtO8efPSOhwRERGp5DToJ1IOxcTEcPz4XwV+aS0OERERERERkdJ144034u3tzYoVK0hLS+Py5cu8+uqr3HTTTfTu3Zvo6GjWr19PamoqO3bsYO/evQwYMACAgQMHsmXLFr7//ntSUlJ46aWX8PDwoFOnThiNRh544AGWLl3K6dOnuXTpEvPnz+euu+4iODi4jI9aREREKipN7ylSzmSvw5GclFZgPa3FISIiIiIiIlK6AgMDefXVV1m0aBHt27fHzc2NW265haVLl1KtWjVeeeUV5syZw+LFi6lVqxaLFy+mcePGAHTo0IEpU6Ywbdo0Ll26RPPmzVm7di3u7u4AjBkzhuTkZPr27YvVaqVjx47Mnj27DI9WREREKjoN+omUM9nrcHRtPYzgwFr51tNaHM6T5lsd98QYbC42LiTq16aIiIhIZZd5TY0c/5Z6f6YaOf4VkfIlLCyMt956K8+yVq1asX379nz3HTRoEIMGDcqzzGQyMXPmTGbOnFkicYqIlKaryY8yTTWwWizEpqSWVlgi8g+6ei1STmWvw5Gfi7HRToymavti6kcAHDr8HWvfm8HER8s4IBEREREpVfG7vnJuf20L7y8mJobExIQC60RFncaqJQBERESkFFxNfhTf9iuOH/+LScsmM6hbKQQlIrlo0E9ERERERESkHCv6EgBmJ0UmIiIiIiLliQb9RERERERERMqxoi4BYLbqaT8RERERkapIg34iIiIiIiIiFYCWABARERERkYJo0E9EpBA3vTuN6rd9TUf/dOr3T+N8WQckIiIiIqXKZ9I4XOLjyAwIJGnxstLvL3IcLuY4Mt0CSWpa+v2JiIiIFNXV5Ec+keNoEH+aJ+/8Hd2aJOIcGvQTESlESMQePAeegyDoHG/knVNlHZGIiIiIlCbT7s8wnj2DtWb+U2mWaH8xn2FMP4PV3Tn9iYiIiBTV1eRHppjP8Ew/Q7t67mw+U4rBiYidS1kHICIiIiIiIiIiIiIiIiLFoyf9RJwsJiaGxMSEfMujok5jsVicGJGIiIiIiIiIiIiIiFR0GvQTcaKYmBgmjBtHclJavnVS01K4cO4iZnOGEyMTEREREREp/8zmDKKiThdYx9fXj+DgYCdFJCIiUnld+fCCv8WCEbBaLBw//pe9jj53RcoXDfqJOFFiYgLJSWl0bT2M4MC8578+evwAm6JXYrFanRydiIiIiIhI+ZWYHM/JkydYOO9FTO6mfOt5+3iwZNkyXYAUEREphn8+vLDl8mWuAeIvX2bS+Mn2evrcFSlfNOgnUgaCA2sRUr1unmUXY6OdHI2IiIiIiEj5l5aejIvBjS6thxIacl2edWLizrBr/zoSExN08VFERKQY/vnwglf4/ZBxES93PwZ1mwHoc1ekPNKgn4iIiIiIiIhUGEEBIfneRCkiIiIlK/vhBaPRCIDRaNTnsEg55lLWAYiIiIiIiIiIiIiIiIhI8WjQT0RERERERERERERERKSC0/SeIiKFOH1zb2qc+Iq0qBT+G5MImqJcREREpFJLv68fhsvx2PwDnNNfSD8M5nhsbs7pT0RERKSoTt/cG1PKZTK8/B3eJz2kH0lxp/n8wAHwKcXgRMROg34iIoUIv+9pwnmaQ0e+Y+2HM5j4aFlHJKXNbM4gKup0gXV8ff20SLWIiEgllTx7rnP7a+jc/kRERESKKvy+p4u8T3LDuZw4/hcvfzeZQd1KISgRyUWDfiIiIldITI7n5MkTLJz3IiZ3U771vH08WLJsmQb+REREREREREREpFzQoJ+IiMgV0tKTcTG40aX1UEJDrsuzTkzcGXbtX0diYoIG/aRMfP3110ydOpU2bdqwZMmSHGU7duxg1apVREVFUb16dYYNG8aAAQPs5Rs2bGD9+vVcunSJRo0aMXv2bJo1awZAeno68+bNY8eOHZjNZm6//XZmz55NUFAQAFFRUcyaNYuff/4ZT09P+vbty6RJk3Bx0TLRIiIiIiIiIiJlTYN+IiUoJiaGxMSEfMujok5jsVicGJGIXK2ggBBCqtct6zBEcnn11VfZvHkzdevm/vk8ePAgU6ZMYenSpdxxxx189913jBo1ivr169OqVSt27drF0qVLWb16NS1btmTdunWMHDmSnTt34uXlxaJFizhw4ABbtmzB29ubp556iunTp7NmzRpsNhtPPPEEDRo04KuvviImJoYRI0YQHBzMo49q3mMRERERERERkbKmQT+REhITE8OEceNITkrLt05qWgoXzl3EbM5wYmRSXF3ndMJn8l/0aQkPXufK9vNlHZGIVGXu7u5s3ryZefPmkZ6enqMsPj6exx57jE6dOgFw++2306hRI/bv30+rVq3YtGkT/fr1o23btgCMHj2ajRs3smfPHrp37862bdtYuHAhderUAWDq1Kn06NGD8+fPc/78eY4cOcL69evx9/fH39+fESNGsH79eg36iUilE3jrzbicO0dmSAhx3/1c+v19ezMu6efIdA8h7rbS709ERESkqLrO6YTH5fOk+ddg14w9Du0T+O3NBKWe4e0HbXx8sZQDFBFAg34iJSYxMYHkpDS6th5GcGCtPOscPX6ATdErsVitTo5OisM1PRmDuw2DJ3inZ5Z1OCJSxQ0ZMiTfsg4dOtChQwf79xaLhQsXLlCtWjUAIiMj6dGjh73cYDDQpEkTwsPDadq0KUlJSfapPgHq16+Pp6cnERERXLhwgdDQUAICAuzlzZo148SJEyQlJeHj41OCRykiUrYMycm4JCViS/Z1Tn/WZFysidiszulPREREpKhc05NxS0vC4pHzbz+zOYOoqNN57uOffhmTLRlPV3dnhCgiaNBPpMQFB9bKd0rAi7HRTo5GRESqshdffBGTycQ999wDQFxcXI5BOwB/f39iY2OJi4uzf38lPz8/e/k/y7K/j4uL06CfiIiIiIhIFZOYHM/JkydYOO9FTO6mXOVbHrnMNT5gtVo185mIk2jQT0RERKSSsdlsvPjii3z00Uds2LABLy8vIOvJvrwYDIZ8yxwpz4+bm5Gr2K1Q2W2aTEZstpJvX0qHzlvFU5XPWfaxGwxZx1/W/ZlMRlwMBgwuYHAp4Pe1y99tubgYyOu0ZdcxGAwOtVVQvZKqU9L9uRgMmExGp5y7klCV32siIlKxpaUn42Jwo0vroYSGXJer3Mv9fuAiYNPMZyJOokE/ERERkUokMzOTadOmcfDgQd577z1CQ0PtZYGBgcTHx+eoHxcXR8OGDQkKCgKy1gXMHiS02WzEx8dTrVo1rFZrnvsC9n3/yWwunT/qsi+OZmRYdXG0AtF5q3iq8jnLPl6bLev4y7q/jAwrmTYbtkywZeZ/MmyZf7eVmU+97Do2m82htgqqV1J1Srq/TJuNjAyrU85dSajK7zUREakcggJC8pz5zGisGDfgVGUxMTEkJiYUWs/X14/g4GAnRCTFpUE/ERERkUrk+eef59ixY7z77ru5pvJs0aIF4eHh9OnTB8iaYiUyMpJ+/fpRp04dAgICiIiIoFatrLVpjxw5gtlspnnz5ly8eJEzZ84QFxdHYGAgAAcPHqRBgwZ4e3s78xBFREREREREpJhiYmKYMG4cyUlphdb19vFgybJlGvirADToJyIiIlJJ/Pzzz3z44Yd88sknuQb8AAYOHMi4cePo0qULYWFhrFq1Cg8PDzp16oTRaOSBBx5g6dKlNG7cGC8vL+bPn89dd91FcHAwwcHBhIWFMXfuXGbNmsXZs2dZu3Ytjz/+uPMPVERERERERESKJTExgeSkNLq2HkZwYK1868XEnWHX/nUkJiZo0K8C0KCfiIiISAXSokULACwWCwC7d+8G4NChQ2zZsoWEhATuvPPOHPu0bt2a119/nQ4dOjBlyhSmTZvGpUuXaN68OWvXrsXd3R2AMWPGkJycTN++fbFarXTs2JHZs2fb21m2bBkzZ87k9ttvx9vbm8GDBzN48ODSP2gRERERERERKRXBgbXynJ5VKiYN+ok4wJG5jaOiTtsvwIqIiJSWQ4cO5Vv2/PPP8/zzzxe4/6BBgxg0aFCeZSaTiZkzZzJz5sw8y0NCQli7dq3jwYqIiIiIiIhImTCbM4iKOp1vua5nV04a9BMphKNzG6empXDh3EXM5gwnRSYiIiIiIiIiIiIiklNicjwnT55g4bwXMbmb8qyj69mVU5kP+h0+fJgFCxYQHh6Oq6srbdq04emnn+aaa65h3759zJ8/n+PHjxMSEsKYMWPo3bu3fd8NGzawfv16Ll26RKNGjZg9ezbNmjUDID09nXnz5rFjxw7MZjO33347s2fPJigoqKwOVSooR+c2Pnr8AJuiV2KxWp0YnTjDLwOep9qp/VyIjOa13/cT1qasIxIRERGR0pS0aAmkpYGHh3P6a7IEMtPAxTn9iYiIiBTVLwOex2hOw+rmeL7yS8rzRJ/5jY++el/X05wsLT0ZF4MbXVoPJTTkujzr6Hp25VSmg34ZGRkMHTqUBx98kLVr15KUlMS4ceOYPXs2s2bNYtSoUUycOJH+/fuzb98+xo8fT7169QgLC2PXrl0sXbqU1atX07JlS9atW8fIkSPZuXMnXl5eLFq0iAMHDrBlyxa8vb156qmnmD59OmvWrCnLQ5YKrLC5jS/GRjsxGnGmcy06c47OHDryHbsjI5WkCFD4FAnZfH39tMixiIhIBZPR7W7n9lfduf2JiIiIFNW5Fp2Lvo+5M5GxnuyO/FjX08pIUEBIvte0dT27cirTQb/U1FQmTJjAfffdh6urK0FBQdx11128+eabfPjhh9StW5chQ4YA0KlTJzp37szmzZsJCwtj06ZN9OvXj7Zt2wIwevRoNm7cyJ49e+jevTvbtm1j4cKF1KlTB4CpU6fSo0cPzp8/T40aNcrsmEVEpOJzZIqEbN4+HixZtkwDfyIiIiIiIiIiIlKqynTQz9/fn/79+wNgs9k4fvw4W7du5e677yYyMtI+VWe2pk2b8umnnwIQGRlJjx497GUGg4EmTZoQHh5O06ZNSUpKyrF//fr18fT0JCIiQoN+IiJSLI5MkQAQE3eGXfvXkZiYoEE/ERERERERERERKVVlvqYfQHR0NN26dcNqtTJgwADGjRvHsGHDaNy4cY56AQEBxMbGAhAXF0dAQECOcn9/f2JjY4mLi7N/fyU/Pz/7/iIijgo4dQg/0++4mP+kRe20sg5HypGCpkgQERGRisv1t18gIwNMJiwtbyr1/pJOfUFqUjyZBjdSPJrmKo+KOo3FYin1OERERETyE3DqEC6WDDJdTcRf28KxfYyHqO1z1OHraYUtpaKcSKRw5WLQLzQ0lPDwcE6ePMmMGTOYPHkyBoMhz7rZ2wsqz6+soP0A3NyMFFBcoOz9TCYjNtvVtSHFVxrnwWQy4mIwYHABg0sBP1suWf0bDIZ865VUnYrQn8v/6ri4GLAVsZ2yjv2fddqtHY7nnHO0agJtWhh593TFOjfZW8rL61lW/ZVV7C4GAyaTEZPp788YfVaULZ0HEREpjN+QQRjPnsFasxaxvx0u1b5iYmIIPjCA67zTuJDkzv3rO+Sqk5qWwoVzFzGbM0o1FhEREZH8tFs7HM/4c6QGhPDp3B8c28dnOJ2an6NHbSPvnCq4riNLqSgnEilcuRj0g6wLp/Xq1WPKlCn069ePO+64g/j4+Bx14uLiCAoKAiAwMDDP8oYNG9rrxMfH4+XlBWRNHxofH0+1atXyjcFsthYj/qx/MzKsuoBYhkrjPGRkWMm02bBlgi0z/0ZtmWCzZf2s5VevpOpUhP4y/1cn8x91nX18Jd0WVLxzk72lvL2eFflnoSj9ZdpsZGRYyciw6rOinNB5EBGR8iQxMYFq//tA8nL3Y1C3GbnqHD1+gE3RK7FYr/5vVhEREZHyzJGlVJQTiRTOpSw7//HHH+nSpUuOR3IzMzMBuPXWW4mIiMhR/+DBg4SFhQHQokULwsPD7WVWq5XIyEjCwsKoU6cOAQEBOfY/cuQIZrOZ5s2bl+YhiYiIiIiIiFwVo9FISPW6ub4C/bUuvYiIiFQN2UupKCcSuTplOujXtGlTUlNTWbx4MampqcTGxrJixQpatWpFr169iI6OZv369aSmprJjxw727t3LgAEDABg4cCBbtmzh+++/JyUlhZdeegkPDw86deqE0WjkgQceYOnSpZw+fZpLly4xf/587rrrLoKDg8vykEVEREREREREREREykxMTAzHj/9V4JfWzxOpmMp0ek8fHx9ee+01Fi5cyO23346rqytt2rRh3rx5VKtWjVdeeYU5c+awePFiatWqxeLFi2ncuDEAHTp0YMqUKUybNo1Lly7RvHlz1q5di7u7OwBjxowhOTmZvn37YrVa6dixI7Nnzy7DoxURERERERERERERuToxMTEkJiYUWMfX16/AB19iYmKYMG4cyUlpBbaj9fNEKqYyX9OvSZMmrF+/Ps+yVq1asX379nz3HTRoEIMGDcqzzGQyMXPmTGbOnFkSYYqIiIiIiIiIiIiIlAlHB+vcTAamTptGYGBgnuVRUae5HJ/E3e1GEhxYK992tH6eSMVU5oN+IiIiIiIiIiIiIiKSv8TEBJKT0ujaeli+g3Unow/z5vZ5zJw+G5O7Kc862U/w+fsEE1K9br79XYyNLpG4RcS5NOgnIiIiIiIiIiIiIlIBBAfWynew7mJsNC4GN7q0HkpoyHV51tETfCKVmwb9REREREREREREREQqiaCAkAIHBkWk8nIp6wBEREREREREREREREREpHj0pJ+ISCF2PfM5xvQkDn/7E698uJiRg8s6IhEREREpTXHf7gebDQwGp/T3r//cSv/OU6hR7Vqn9CciIiJSVLue+bzI+dGuy58T8ef3vLFlnq6niTiJBv1ERAph8fDBgg9JxiCS0/WAtIiIiEhlZ/PxdWp/qWZXzJneWPBxar8iIiIijrJ4FD1PseBDhtVL19NEnEjvNhEREREREREREREREZEKTk/6SZUXExNDYmJCvuVRUaexWCxOjEhERERERERERERERKRoNOgnVVpMTAwTxo0jOSkt3zqpaSlcOHcRsznDiZFJedLg81epcd1ewoxxcEdcWYcjFYzZnEFU1Gkga9r7y5d9iI1Nwmb7u46vrx/BwcFlFKGIiIj8k+fqlRgSE7D5+pE66olS72/AjSdpXe113N1r82f6iFLvr7K7Mv8qiHIwERERxzX4/FXc0pIwe/jwZ2fH8pUG7q8SVPt3XU8TcSIN+kmVlpiYQHJSGl1bDyM4sFaedY4eP8Cm6JVYrFYnRyflxQ1fvIZnp3PUCIJ/32DknVNlHZFUFInJ8Zw8eYKF817E5G4CwNXViMWS8/eJt48HS5Yt00UnERGRcsJzzUqMZ89grVnLKYN+D9x4kmt8jpKaGaJBv2LKK//Kj3IwERERx93wxWt4xp8jNSDE4UG/Gzxew7P2ORr56HqaiLNo0E8ECA6sRUj1unmWXYyNdnI0IlJZpKUn42Jwo0vroYSGXAeAm5sRs/nvQb+YuDPs2r+OxMQEXXASERERKaa88q+8KAcTERERkcpIg34iIiKlLCggxH5jgcnkSkaG1gkVERERKU1X5l8iIiIiIlWFS1kHICIiIiIiIiIiIiIiIiLFo0E/ERERERERERERERERkQpOg34iIiIiIiIiIiIiIiIiFZwG/UREREREREREREREREQqONeyDkBERERERESksoqJiSExMSHf8qio09SzOTEgERERERGptDToJ5WaI39gWywWJ0YkIiIiIiJVRUxMDBPGjSM5KS3fOqlpKXw43OrEqEREREREpLLSoJ9UWo7+gX3h3EXM5gwnRiYVTXzt5hjPp2BNsnIoQbdhi4iIiFR2lrCWZNYKJTM4uFjtJCYmkJyURtfWwwgOrJVnnaPHD3Ao6hdsbjdgcAstVn8iIiJSMRX24AKU/cML8bWbkxJQkwyfao7vY2lOTLovv0dFl2JkInIlDfpJpeXoH9iboldiserOWsnfvsfWAXDoyHesfW8GEx8t44BEREREpFQlvPVeibYXHFiLkOp18yy7GBvNo+tqMfHRpVxXp3GJ9isiIiLlnyMPLkDZP7yQfX2sSPskr9P1NBEn06CfVHqF/YEtIiIiIiIiIiIiUhYceXAB9PCCiDhGg34iIiIiIiIiIiIiImWooAcXQA8viIhjXMo6ABEREREREREREREREREpHj3pJyJSiHZrhlGtz4/cXctKu2E2DmWWdUQiIiIiUpr8HhqAS0wMmcHBJb6+X17eGHaG5teNx+AWyr7koq+XIyIiIlLa2q0ZhinpEhk+1Rxe36+d9zBaNztJu2FndD1NxEk06CciUoiAqHBMNRIgCFrEGzl0qqwjEhEREZHS5HrwN4xnz2Ctmf+6OiWpRe10anr/TmpmnFP6ExERESmqgKhwPOPPkRoQ4vg+ruF4ms7hWlvX00ScRdN7ioiIiIiIiIiIiIiIiFRwetJPRESkjJnNGURFnS6wjq+vH8HBwU6KSERERERERERERCoaDfqJiIiUocTkeE6ePMHCeS9icjflW8/bx4Mly5Zp4E9ERERERERERETyVORBv8zMTF5//XV69uxJzZo1SUpK4vnnnyciIoJbbrmFyZMnYzLlf9FSRERE/paWnoyLwY0urYcSGnJdnnVi4s6wa/86EhMTNOhXQSl/EhEREXEe5V4iIiJSVRV50O/ll1/mrbfeomPHjgC88MIL7Nmzh/vuu49du3bh6enJxIkTSzxQERGRyiwoIISQ6nXLOgwpJcqfRERERJxHuZeIFFdMTAyJiQmF1vP19aN6dd2cKyLlR5EH/bZv386cOXOoX78+aWlpbN++nVmzZtG3b186dOjArFmzlDiJiIiIXKGk86evv/6aqVOn0qZNG5YsWZKj7OOPP2b58uWcOXOGunXrMm3aNG677TYg6673ZcuWsXnzZpKSkrjpppuYM2cOderUASAuLo7nnnuOr776CqPRSLdu3ZgxYwYeHh4A/P777zz77LNERkYSEBDAo48+yqOPPlpCr5KIiIhIydC1KxEpjpiYGCaMG0dyUlqhdb19PFi6fBnBwb5OiExEpHBFHvQ7f/48YWFhAOzfvx+LxULXrl0BuO666zh//nzJRigiIiJSwZVk/vTqq6+yefNm6tbN/WRoeHg4U6dO5YUXXqBTp058+OGHjB49mh07dhASEsKbb77Jli1bWLduHbVr12bhwoWMHj2a7du3YzAYmD59OsnJyezcuROr1cqoUaN48cUXeeaZZ0hNTWXEiBH07t2bdevW8ccffzBixAhCQ0Pp1q1bybxQIiIiIiVA165EpDgSExNITkqja+thBAfWyrfelUtxiIiUFy5F3cHPz4/4+HgAvvnmG8LCwvD1zbqTIT4+Hk9PzxINUERERKSiK8n8yd3dPd9Bvy1bttChQwd69OiBh4cH/fv3p2HDhmzfvh2ATZs2MXz4cBo3boyPjw9Tp07lr7/+4tdffyUmJoYvvviCadOmERwcTI0aNRg/fjxbtmwhIyODL7/8ErPZzKRJk/D29ubGG29kwIABvPfee8V/gURERERKkK5diUhJCA6sRUj1uvl+FTQgKCJSVor8pF/r1q1ZsGAB7du35/333+fJJ58EsqaLeuutt2jWrFmJBykiUpb+6DicGsf3kngsjv9En8Hn+rKOSEQqmpLMn4YMGZJvWWRkJB06dMixrWnTpoSHh5Oens6xY8do3ry5vczHx4drr72W8PBwkpKScHV1pVGjRvbyZs2akZKSwvHjx4mMjKRx48YYjcYcbW/atMnh2EVEKorUx57AkJiAzdfPKf2t/TKAru3uxse3nlP6E6nsdO1KRKTk/dFxOG5pSZg9fBzfJ204sbG/89VPX+p6moiTFHnQb/LkyTz55JOsXLmSrl27MnjwYAA++ugjPvnkEzZs2FDiQYqIlKU/O4/gT0Zw6Mh3rP1qBhOVpIhIETkrf4qLiyMgICDHNn9/f/744w/i4+Ox2Wz4+/vnKo+NjcXf3x8fHx9cXFxylAHExsYSFxeXa9+AgADi4+PJzMzMsV82NzcjBkOJHFoO2W2aTEZstpJvX0qHzlvFU5XPmXXcOPv/TcVox2Qy4mIwYHABg0vevxANLrB2byC+9YdwnUdjDHnMx2NwyTofBoMh33aurAfg4mIgr9NW1LYKqldSdcqqPxeDAZPJiMlkzLeeM1Tl91pp0bUrEZGS92fnEUXfJ30Eh6K+Y+1Xv+l6moiTFHnQr1atWrzzzju5tt9xxx18+umnGErjyo6IiIhIBeas/Cm/dgpr32AwFFinsPL8mM3WIu/jiOxQMjKsujhagei8VTw6Z8WXkWEl02bDlgm2zLxfRFsm2Gxgs9mKVefKegCZJdRWceMqz/1l2mxkZFjJyCidzytH6b1W8koj93r55Zd55513SE5OpmXLlsyZM4c6deqwb98+5s+fz/HjxwkJCWHMmDH07t3bvt+GDRtYv349ly5dolGjRsyePdv+pGF6ejrz5s1jx44dmM1mbr/9dmbPnk1QUNDVH7yIiEgpMJsziIo6XWAdX18/goODnRSR5KfIa/o1adKE2NjYXNv9/f2Jj4/ngQceKJHARERERCoLZ+VPgYGBxMXF5dgWFxdHUFAQgYGBuLi42Ne3ubK8WrVqBAUFkZiYiNVqzVEG2Mvz2je7XREREZHyoqRzr3feeYc9e/bw3nvv8eWXX1KzZk3eeOMNzp8/z6hRo+jXrx8//vgj06ZN45lnnuHgwYMA7Nq1i6VLlzJ//nx++OEH7rjjDkaOHElKSgoAixYt4sCBA2zZsoXPP/+ctLQ0pk+fXvwXQEREpAQlJsdz8uQJFs57kUnjJ+f7NWHcOGJiYso63CrP4Sf9/vvf/wJZd8t98skn+PjknLvXZrPx448/kpCQUKIBioiUNde0JIwk4WONxds9s6zDEZEKxNn5U4sWLYiIiMix7dChQ/Ts2ROTyUTDhg2JiIigdevWAMTHx3Pq1ClatGhBnTp1yMzM5MiRIzRt2hSAgwcP4uvrS7169WjRogUbN27EYrHg6upqLw8LCyuR2EVEyhNDUmLW42IGAzYf31Lvz9s9E5NLMq4kYcHxdXJEJKfSyr3WrVvHSy+9RGhoKADz588H4LXXXqNu3br2NZc7depE586d2bx5M2FhYWzatIl+/frRtm1bAEaPHs3GjRvZs2cP3bt3Z9u2bSxcuJA6deoAMHXqVHr06MH58+epUaPGVb8OIuI82U8/BQX5EBublOcT25Xl6SfXtCR7fmRxcF0/V5IwGVN0Pa2CS0tPxsXgRpfWQwkNuS7POjFxZ9i1fx2JiQmV4ue9InN40G/Lli2Eh4djMBiYO3duvvUefPDBEglMRKS86Dq3M55zztHzNhjczMg7p8o6IhGpKJydP/Xv359+/frxySef0KlTJzZt2sSpU6fo06cPAIMGDWLlypW0bduW0NBQ5s6dS/Pmze0Dd3fffTfz589nyZIlpKens2TJEgYMGICbmxsdOnTA29ubxYsX88QTTxAREcH777/P0qVLSyR2EZHyJPC21hjPnsFasxaxvx0u9f6+euokNQP6kpoZwqeXfyj1/kQqq9LIvc6fP8+5c+c4efIkkydP5vLly7Rr145Zs2YRGRlpn6ozW9OmTfn0008BiIyMpEePHvYyg8FAkyZNCA8Pp2nTpiQlJeXYv379+nh6ehIREaFBP5EKIPvppwVzX8TL2xOLJe/por19PFiybFmFHwjpOrcznvHnSA0I4dO5juUrXf0707v1OR65QdfTKoOggBBCqtct6zCkEA4P+r311ltYLBaaN2/Of/7zHwIDA3PV8ff3p1q1aiUaoIiIiEhFVRr5U4sWLQCwWCwA7N69G8h6oq9hw4a8+OKLLF68mKlTp1K/fn1eeeUV+x+XAwcO5OLFiwwdOpTk5GTatGnD8uXL7W0/++yzzJ49m65du+Lm5kavXr0YN24cACaTiVdeeYWZM2fSrl07qlWrxpQpU7jjjjuu7sURERERKWGlkXudO3cOg8HA7t27ee+990hLS2Ps2LHMmDGD5ORkGjdunKN+QECAfWrRuLg4AgICcvUfGxtrn0bd398/R7mfn1+eU5OKSPlz5dNP9eo0yHNNcz39JCLO5vCgH4Crqyuff/45tWrVuqpFj/MSFRXFvHnz+PnnnzEajdx+++08/fTTJCYm0rlzZ0wmU47648ePZ9iwYQB8/PHHLF++nDNnzlC3bl2mTZvGbbfdBkBmZibLli1j8+bNJCUlcdNNN9kXWRYRERFxlpLOnw4dOlRgebdu3ejWrVu+5WPGjGHMmDF5lvn6+rJ48eJ8973hhht49913HQtURKSSi4mJITGx4CkCo6JO22/SEBHnKOncy2w2YzabmTx5sn0QcezYsYwYMYJbb701z32y+82vf4PBUGBs+ZW5uRkpoctx/+gv61+TyZjn1IRS9nSOnMtkMuJiMGBwAYNLAe9Vl6xzUy2wJjWvqYfFYuWfp8fgAi4GAyaTEZPJWCL9GQyGfOuVVJ3C6mV/72hbULz+iht7dk0XF4P9HDnrtXLG8ZWX/gr7Wc+3ff2OK1FFGvQDCA0N5aeffuLgwYNcvnwZ2z/OgsFgYMKECQ63N2rUKJo3b84XX3xBcnIyo0aN4oUXXmDUqFFA/he2wsPDmTp1Ki+88AKdOnXiww8/ZPTo0ezYsYOQkBDefPNNtmzZwrp166hduzYLFy5k9OjRbN++vcQGLEVEREQcUdL5k4iIlK2YmBgmjBtHclJagfVS01K4cO4iZnOGkyITESjZ3Cv7Sb0r1wcMDQ3FZrNhNpuJj4/PUT8uLo6goCAAAgMD8yxv2LChvU58fDxeXl5A1pqD8fHx+T6JmNdTRCUh+zJZRoZVF1vLKZ0j58rIsJJps2HLBFtm/i+4LTNribvs3zGZedS1ZUJ6Rjp//XWCjIy838NRUafJMJuL1F9+9UqqTmH1sr93tC0oXn/FjT275pXnyFmvVVXqL9NmIyPDmu/Pen70O65kFXnQb9WqVaxYsSLf8qIkTomJiTRv3pwnn3wSb29vvL296du3Lxs2bLAP+uVny5YtdOjQwT43ev/+/dm0aRPbt29n5MiRbNq0ieHDh9unWZg6dSpt27bl119/5aabbnLwaEVERESKryTzJxERKXuJiQkkJ6XRtfUwggNr5Vvv6PEDbIpeicVaOhfqRSRvJZl71a1bFx8fHyIiImjfvj0A0dHRuLq6cuedd7J9+/Yc9Q8ePGhfL7lFixaEh4fb11e2Wq1ERkbSr18/6tSpQ0BAABEREdSqlfV75MiRI5jNZpo3b17UQxaRcip73b+F817E5G7Ks45uEhKRklTkQb/333+fhx9+mFGjRuWal7yofH19mT9/fo5tZ86csd/tBDB58mS++eYb3N3dueeeexg3bhxubm5ERkbSoUOHHPs2bdqU8PBw0tPTOXbsWI4kycfHh2uvvZbw8HAN+omIiIhTlWT+JCIi5UdwYC1CqtfNt/xibLQToxGRbCWZe7m5udG/f39efPFFGjRogNFoZNWqVdx777306dOHl19+mfXr1zNgwAC++uor9u7dy/vvvw9krac8btw4unTpQlhYGKtWrcLDw4NOnTphNBp54IEHWLp0KY0bN8bLy4v58+dz1113ad0vkUrkynX/QkOuy7OObhISkZJU5EG/y5cv8/DDD5fKBatDhw7x1ltvsWLFCkwmEzfddBNdu3blueee448//mDMmDG4uroyfvz4fBdD/uOPP4iPj8dms+VaDDl7seT8FGdudM07Wz5ceR4cmQ+7KsylXFb9ufyvzpVzZZfF8ZV0W1Dxzk32lvL2elbkn4WymEP+audFl9zK4jO7NPMnEREREcmppHOviRMnsmDBAnr37o2LiwudOnVi+vTp+Pj48MorrzBnzhwWL15MrVq1WLx4sX3WqQ4dOjBlyhSmTZvGpUuXaN68OWvXrsXd3R3IWms5OTmZvn37YrVa6dixI7Nnzy6RmEWkfAkKCMn3RiHdJCQiJanIg37NmjXjxIkT9qkHSsrPP//MqFGjmDRpEnfccQcAGzdutJeHhYXx73//mzVr1jB+/PgCF0MuSEHlxZkbXfPOlg9XngdH5t+uCnMpl1V/2XNk/3M+c2cfX0m3BRXv3GRvKW+vZ0X+WSiLOeSvdl50ya0sPrNLK38SERERkdxKOvcymUzMnDmTmTNn5ipr1apVrik+rzRo0CAGDRpU5HZFRERErkaRB/2ee+45nnvuOcxmMy1btrQvNnwlkynv+Ynzs2fPHiZPnszMmTO59957861Xu3ZtYmNjsdlsBAYGEhcXl6M8e7HkwMBAXFxc8lwsOb/FkEVERERKS2nkTyIiIiKSN+VeIiIiUlUVedBv4MCBWCwWHnvssTzLDQYDkZGRDrd34MABnnrqKZYvX85tt91m375v3z4OHTrEv//9b/u248ePExoaisFgoEWLFkRERORo69ChQ/Ts2ROTyUTDhg2JiIigdevWAMTHx3Pq1ClatGhRlMMVERERKbaSzp9EREREJH/KvURERKSqKvKg3+DBg3FzcyuRzi0WC8888wxTpkzJMeAHEBAQwIoVK6hduzbdunUjMjKSdevWMXz4cAD69+9Pv379+OSTT+jUqRObNm3i1KlT9OnTB8iaPmHlypW0bduW0NBQ5s6dS/PmzQkLCyuR2EWk6tj379fwO/87URF/subHj+natawjEpGKpiTzJxERKX0Jb74LGRngpCeBHl1XkyH3TiLkmhuc0p9IZafcS0QKEhMTQ2JiQr7lUVGnsVgsToyoYtj379dwsWSQ6ep4frQv6TWOn/qZTZ+9qutpIk5S5EG/CRMmlFjnv/76K8eOHePZZ5/l2WefzVG2Y8cOXnrpJVasWMH06dO55ppreOSRR3jooYcAaNiwIS+++CKLFy9m6tSp1K9fn1deeYXg4GAg666uixcvMnToUJKTk2nTpg3Lly8vsdhFpOqIv7YF8bTg0OXvOBT1OcpRRKSoSjJ/EhGR0mdpeZNT+zsU5cHZlKZ4WBs7tV+Rykq5l4jkJyYmhgnjxpGclJZvndS0FC6cu4jZnOHEyMq/+GuLPoNevLUFUUmJHIry0PU0EScp8qAfgNlsZvfu3Rw4cIBLly7x9NNPU61aNY4cOUKjRo0cbqdVq1YcOXIk3/LQ0FC6FnALQLdu3ejWrVu+5WPGjGHMmDEOxyMiIiJSWkoqfxIRERGRwin3EpG8JCYmkJyURtfWwwgOrJVnnaPHD7ApeiUWq9XJ0YmIFF+RB/3Onz/P0KFDOXbsGP7+/iQmJjJhwgTi4uK4//77Wb9+Pa1atSqNWEVEREQqJOVPIiIiIs6j3EtEChMcWIuQ6nXzLLsYG+3kaERESo5LUXdYuHAhRqORbdu28cMPP+Du7g5AgwYNeOihh1ixYkWJBykiUpZCDn1Os5ML6GR5ly5Nk8s6HBGpgJQ/iYhULKadn2L6YBumnZ86pb8uTZNp6L+XELfPndKfSGWn3EtEpOSFHPqc0AMfE3LI8XwlxO1zmgZ9r+tpIk5U5Cf9vv32W1atWkWTJk1ylfXr14+BAweWSGAiIuXFTe9Nx3POORoFQYPmRt45VdYRiUhFo/xJRKRi8Zk8AePZM1hr1iK2292l3t+C/heoGTCP1MwQPr38Q6n3J1LZKfcSESl5N703Hc/4c6QGhPBpC8fylZu8pnNrw3O0v0bX00ScpchP+qWmphIUFJRnmcFgICNDC5yKiIiIXEn5k4iIiIjzKPcSERGRqqrIg37169dn06ZNeZZ9+umn1K9fv9hBiYiIiFQmyp9ERETKH7M5g6io0xw//le+XzExMWUdplwF5V4iIiJSVRV5es8RI0YwceJEfvvtN2655RasVivvv/8+J0+eZPfu3SxevLg04hQRERGpsJQ/iYiIlC+JyfGcPHmChfNexORuyreet48HS5YtIzg42InRSXEp9xIREXG+7BuqCuLr66e8qpQVedCvR48eZGZmsmbNGtasWQPAq6++yg033MCiRYu4++7SX+9AREREpCJR/iQiIlK+pKUn42Jwo0vroYSGXJdnnZi4M+zav47ExARdnKpglHuJiIg4l26oKj+KPOgHcM8993DPPfeQlJREcnIyvr6+eHl5lXRsIiIiIpWG8icREZHyJygghJDqdcs6DCkFyr1EREScRzdUlR8ODfplZGRgMpns/89mMpny3S4iIiJSlSl/EhEREXEe5V4iIiJlTzdUlT2HBv1atmzJN998Q7Vq1QgLC8NgMORb12AwEBkZWWIBioiIiFREyp9EREREnEe5l4iIiIiDg36jR4+2T4EwevToAhMnEWeIiYkhMTEh13aDAS5f9iE2NomoqNNYLJYyiE5ERET5k4iIiIgzKfcSEcj/mmE2XS8UkcrOoUG/J554wv7/MWPGlFowIo6IiYlhwrhxJCel5Vnu6mrEYrGSmpbChXMXMZsz8qwn4iiLuze2dAO2VEhOdynrcESkglD+JCJScdm8vcn08cXm7e2U/pLTXUi3umPBOf2JVEbKvUSksGuGgK4XFoPF3Ruzhw8Wd8fzFYvNm3SLJ8npGmgVcRaHBv2++eabIjXavn37qwpGxBGJiQkkJ6XRtfUwggNr5Sp3czNiNls5evwAm6JXYrFayyBKqUx2zdgDwKHfvmPtezOY+GgZByQiFYLyJxGRiivuu5+d2t8dC+oy8dFVXFensVP7FalMlHuJSGHXDAFdLyyG7OtjRdonYQ+Hjuh6mogzOTToN3z4cAwGAzabrdC6BoOB33//vdiBiRQmOLBWnouCmkyuZGRYuBgbXQZRiYiIZFH+JCIiIuI8yr1EJFt+1wwBXS8UkUrPoUG/N998s7TjEBEREalUlD+JiIiIOI9yLxEREREHB/1uueWWXNusVitGo9H+fWpqKp6eniUXmYiIiEgFpvxJRKTiiomJITExId/yqKjTWCxam0akPFHuJSIiIuLgoN+VUlJSmD59Oj4+PsydO9e+fcSIEQQHB/P888/j5eVVokGKiJSl5tvmUePGr7jNK4VreiWSUtYBiUiFo/xJRKTiiImJIeLurnikppJodOPleg1z1UlNS+HCuYuYzRkl0uczvWJoX3sJ7p7XEp76dIm0KVKVKfcSESl5zbfNw5RymQwvf8Lvcyxfae45j3rX/8E1vWJ0PU3ESVyKusNLL73EgQMHuOOOO3Jsf/jhhzl06BBLliwpseBERMqDOj9/gH+9I9QIO02f/0ss63BEpAJS/iQiUnEkJibQ4WwU91w4Q6+kFAZ1m5Hrq32L/litmVis1hLps8//JdIiaAd1TB+USHsiVZ1yLxGRklfn5w/4//buPD6q6vzj+HcmZAgkIQsBwhIioqxJFAsCRVFQqFJFtCCgLVWUIkVkUVkUEQuKCMiiVkFRlqpgoIhU5Se4V1FRqpAEUZEtYCBDMmQSssxk5vcHTUokywzJrPm8Xy9eOvece89zc0PycJ57z71gx3olfON6vpJgekuXNf+Q+TTAi9wu+r333nt66qmnNGDAgArbBwwYoMcff1zvvfdenQUHAAAQDMifACAwhYSEKL5Z4jl/YqJa+Do0ANUg9wIAAPWV20U/i8Wili1bVtrWvHlzWSyW2sYEAAAQVMifAAAAvIfcCwAA1FduF/0uuugivfVW5Y/wvvbaa2rfvn2tgwIAAAgm5E8AAADeQ+4FAADqqwbu7nDvvffq3nvv1WeffaauXbuqYcOGslgs2rVrlw4fPqxnnnnGE3ECAAAELPInAAAA7yH3AgAA9ZXbRb/+/ftr5cqVevnll/Wvf/1L+fn5ioiIUEpKih599FH17t3bE3ECAAAELPInAAAA7yH3AgAA9ZXbRT9J6t27NwkSPMZsNstqzauyPTPziOx2uxcjAgCg9sifAAAAvIfcCwAA1EfnVfQDPMVsNmvyxIkqyC+qsk9h0WmdyMqWzVbixcgAAAAAAAAAAAD8F0U/+BWrNU8F+UUa0OMuxcW0qrTPDwd2KfXos7KXlno5OgDwHZutRJmZR2rsFxnZRHFxcV6ICAAAAAAAAIA/oegHvxQX00rxzRIrbcvOOerlaFDfZXXtr2ZHPpXteLHezy2SInwdEeoba4FFhw4d1PzHF8rU0FRt3/CIMC1eupTCHwAAtbAjOk5d4y5WSBU3Ita19zPC1aPLJTI1SvDKeAAAAO7K6tpfoactsjWOdn0fW3+dzt+v/+zby3wa4CUU/QCgBv8ZOU+StGff51qR+oim3OnjgFDvFBUXyGgI1bU9Rqt1fLsq+5lzj2nbzpWyWvMo+gEAUAsL23fRyIGPVHkjYl2bltpcU+6cqXYJnbwyHgAAgLvK5sfc2uf0PO35kfk0wJso+gEAECBio+O9NvkIAAAAAAAAILCcV9Hv4MGDWr16tXbt2qWTJ09q/fr1atasmTZu3KiRI0fWdYwAAAABj/wJAPyD2WyW1ZpXZXtm5hHZ7XYvRgTAE8i9AABAfeR20e8///mP7rzzTkVERKhbt27av3+/HA6HfvnlFz311FNq0KCBhg0b5olYAQAAAhL5EwD4B7PZrMkTJ6ogv6jKPoVFp3UiK1s2W4kXIwNQl8i9AABAfeV20e/pp59Wv379NH/+fJlMJnXr1k2SlJiYqBkzZujVV18lcQIQVPrNv0FR4/bqpk5ODZnSQNtzfR0RgEBD/gQA/sFqzVNBfpEG9LhLcTGtKu3zw4FdunPPNF24bITsMS314bR/eTyud6Yc0YUtbpfd2FIfWj0/HhDsyL0AoO71m3+DwqzZKops5nJ+1C/yBl3b7aiGtC5gPg3wEqO7O+zZs0d//etfZTKZzmn77W9/q0OHDtVJYADgL8Ks2TJG2hUSXarmkSz1BMB93s6f0tPTNWrUKHXv3l2//e1vNXXqVOXmnvkX1o4dOzR48GAlJydrwIABeuuttyrsu3r1avXr108pKSkaNmyY0tPTy9uKi4s1a9YsXX755erWrZvuu+8+5eTk1GnsAOANcTGtFN8ssdI/MVEt1NxhV2S+WWHWbK/E0zzSrkiTWWFG74wHBDvmrgCg7oVZs9XIkuVWfhRmzFaThjnMpwFe5HbRz2g0ymazVdqWl5cno9HtQwIAAAQ1b+ZPpaWl+stf/qJu3brp888/1zvvvCOz2azZs2fr+PHjGjdunIYOHaqvvvpKM2bM0MyZM7V7925J0rZt27RkyRLNmzdPX375pa666iqNHTtWp0+fliQtWLBAu3bt0saNG/X++++rqKhIDz30UJ3FDgAAUBeYuwKCj9ls1oEDP1f7h/fyAsB5LO/ZrVs3LVy4UEuXLlVkZGT5dpvNphdeeKF8yQQAAACc4c38KTs7W2azWTfeeKNMJpNMJpOuueYarVq1Slu2bFFiYqJGjRolSerfv7+uueYabdiwQSkpKUpNTdXQoUPVq1cvSdL48eO1bt06ffDBB7ruuuu0adMmzZ8/XwkJCZKkadOmadCgQTp+/LhatGhRZ+cAAABQG8xdAcHFlXfySryXFwCk8yj6TZkyRX/84x919dVXq2PHjrLZbHr44Yd18OBB5efn6x//+Icn4gQAAAhY3syfWrRooS5duuiNN97Q5MmTVVhYqG3btunqq69WRkaGunbtWqF/ly5d9O6770qSMjIyNGjQoPI2g8Ggzp07Ky0tTV26dFF+fn6F/du3b69GjRopPT2doh8AAPAbzF0BwcWVd/JKZ97Lm3r0WdlLS70YHQD4F7eLfl27dtXmzZv1yiuv6LvvvlOrVq10+vRpDRw4UKNGjVLbtm09ESeCgNlsltWaV20fHsMHAAQjb+ZPBoNBy5Yt0x133KHVq1dLknr27KkpU6bor3/9qzp16lShf3R0dPl7+XJzcxUdHV2hPSoqSjk5OeXvBIyKiqrQ3qRJkyrf6xcaGiKDoS7OqqKyY5pMIXI66/748AyuW+AJxmtmMoXIaDDIYJQMxsp/QBmMv/58bj+D8czXx2AwVHkcV/t5YjxJMhoNquyy1XXsddHHn8czGgwymUJkMoVUeazaCsa/a77G3BUQnMreyVuV7JyjXowGAPyT20U/SWrbtq0effTRuo4FQYzH8AEA9Z238qeSkhKNHTtWgwYN0j333KPCwkLNmjVLDz74oAxVVODKtlfXXlVbdfvZbJ65w7ZsuJKSUiZHAwjXLfAE4zUrKSmVw+mU0yE5HZWflNPx68/n9nM6JKdTcjqdVR7H1X6eGE+SHNWMV5ex10Uffx7P4XSqpKRUJSWee2okGP+u+QPmrgAAQH3kUtFv586dLh/Qbrerd+/e5x0QghOP4QMA6htf5U+ff/65MjMzNWnSJIWEhCg8PFwTJkzQkCFDdNVVV8lisVTon5ubq9jYWElSTExMpe0dOnQo72OxWNS4cWNJZyZKLRaLmjZtWiexAwAAnC/mrgAAAFws+v3pT38qv4Pb6XRWe6e3JO3du7f2kSEo8Rg+AKC+8FX+5HQ65XBUfGzEZrNJknr37q1NmzZVaNu9e7dSUlIkScnJyUpLS9OQIUMkSaWlpcrIyNDQoUOVkJCg6Ohopaenq1WrMzfw7Nu3TzabTUlJSXUSOwAAwPli7goAAMDFot+aNWvK/z83N1cLFizQ1Vdfrcsuu0xRUVGyWCz68ssv9eWXX2r27NluBZCZmanHH39c33zzjUJCQnTllVfq4YcfVlRUlPbu3avHHntMGRkZio6O1p133qk777yzfN+3335by5Yt07Fjx5SYmKgZM2aoT58+kiSHw6GlS5dqw4YNys/PV7du3TRnzhwlJCS4FR8AAMD58GT+VJ1LL71U4eHheuaZZ3TPPfeouLhYL774orp166bBgwfr2Wef1apVqzR8+HB9/PHH+uSTT/TGG29IkkaMGKGJEyfq2muvVUpKip577jmFhYWpf//+CgkJ0a233qolS5aoU6dOaty4sebNm6ff/e53iouLq7P4AQAAzoevci8AAAB/4lLR7/LLLy///8mTJ2vs2LEaNmxYhT6///3v9frrr2vdunVuLZEwbtw4JSUl6cMPP1RBQYHGjRunp556SjNnztSYMWM0ePBgrVy5Uj/++KPGjBmj1q1ba+DAgUpLS9O0adP01FNPqX///tqyZYvGjx+vrVu3Kj4+XmvWrNHGjRu1cuVKtWnTRvPnz9f48eO1efPmGu/2AoCz7blphpod2qGc74/r5f0ZuvASX0cEIBB4Mn+qTkxMjF588UUtWLBAV1xxhUJDQ3X55ZdryZIlatq0qZYvX645c+Zo0aJFatWqlRYtWqROnTpJkvr27aupU6dqxowZOnnypJKSkrRixQo1bNhQkjRhwgQVFBTolltuUWlpqfr168ekGYCgNDciTjf9dqSiW7Tzznhb4nRTv5GKjvbOeEAw8lXuBQD1xZ6bZqiBrVD20Eau73N6hrKOp+n/Pn+L+TTAS1wq+p3t008/1eTJkytt++1vf6uFCxe6fCyr1aqkpCQ98MADCg8PV3h4uG655RatXr1aH330kWw2m+6//36FhITo0ksv1fDhw7V+/XoNHDhQGzduVN++fTVo0CBJ0rBhw5SamqrNmzdr7NixSk1N1d13310+iTVt2jT16tVL3377rbp16+buaQOoxzJ7DFGmhmjPvs/15q5HNIUkBYCb6jJ/ckVKSorWrl1baVv37t21efPmKvcdOXKkRo4cWWmbyWTSrFmzNGvWrDqJEwD81ZthkbrwkuvVLqGTd8bb9d/xwr0zHhDsvJ17AUB9kNljiPv72IZoT3ZzvbnrQ+bTAC8xns9OaWlplW53dz30yMhIzZs3T02bNi3fduzYMcXGxiojI0OdOnVSSEhIeVuXLl3Kx87IyFDXrl0rHK+svbi4WPv376/wfpmIiAi1bdu2ytgBAAA8qa7yJwAAANSM3AsAANRHbj/p179/f82cOVPfffedkpKS1KRJExUVFWnv3r169dVX1bdv3/MOZs+ePVq7dq2eeeYZbdu2TVFRURXao6OjZbFY5HA4lJubq+jo6ArtUVFR+vHHH2WxWOR0Os/ZPyoqSjk5OVWOHxoaovNd+bNsP5MpRE7n+R0jmJlMITIaDDIYJYOx6i+ywXjma2kwGKrsV12fsk9Go6HWx3KnT10eK1jGM/63j9FokNPN4/g69mAbr2xLsJ5fIMV+9s8oZxV9ajue0WCQyRQikymkyn71nS9+Z3syfwIAAEBF5F6AfzCbzbJa82rsFxnZhPeEA0Adcbvo9+ijj8pgMOj1119XSUnJ/w7UoIH69+9/3u91+eabbzRu3Djdf//9uuqqq7R9+/Zq+1f1Xr6a3tdXXbvNVlpzoFUe98x/S0pKKfpVoqSkVA6nU06H5HRU/QVyOiSnU3I6nVX2q65P2SeHw1nrY7nTpy6PFSzjOf7bx/Hra+Tl86uLY0Uc36/wBgd1UfFeXRhXEnDXpmyLv3w9fTWeP8R+9s8oT43ncDpVUlKqkpLz/50W7HzxO9tT+RMA4H9cmVjMzDwiu91e47Ha20vUNPugIkyhym/Rvq5CrHq8ZiVq2vCgIoyhynd4fjwg2JF7Ab5nNps1eeJEFeQX1dg3PCJMi5cupfDn5yKO75fBUSqnMcTl/CjCuF/NGh1R+2YlNXcGUCfcLvqFh4dr/vz5euyxx3Tw4EHl5+ercePGSkxMVHh4+HkF8cEHH+jBBx/UrFmzdNNNN0mSYmNjdejQoQr9cnNzFRMTI6PRqJiYGOXm5p7THhsbW97HYrGc0372UqIA4Iorn7lNjeZkqc9FUr/kEL122NcRAQg0nsifAAD/4+rEYmHRaZ3IypbNVv3E03rLUbV8eawKo+P17twv6zLUysf761G1jB6rQke83j3l+fGAYEfuBfie1ZqngvwiDehxl+JiWlXZz5x7TNt2rpTVmkfRz89d+cxtamTJcis/ujLyNg28JEs3JzKfBniL20W/MmFhYerUqfYvGd+1a5emT5+uZcuWqU+fPuXbk5OTtW7dOtntdjVocCbM3bt3KyUlpbw9PT29wrH27Nmj3//+9zKZTOrQoYPS09PVo0cPSZLFYtHhw4eVnJxc65gBAADOR13lTwCAilydWPzhwC6lHn1W9lKeiAfqA3IvwPfiYlopvlmir8MAgHrD6MvB7Xa7Zs6cqalTp1Yo+ElS3759FR4erkWLFqmgoEBfffWV3njjDd1+++2SpGHDhumzzz7TO++8o6KiIq1du1aHDx/WkCFDJEkjR47USy+9pO+//15Wq1Vz585VUlJSedEQAAAAABBcyiYWq/oTE9XC1yECAAAAgMec95N+deHbb7/V/v379dhjj+mxxx6r0LZ161YtX75cs2bNUu/evdW0aVNNnTpVV111lSSpQ4cOWrhwoRYtWqRp06apffv2Wr58eflj4CNGjFB2drZGjx6tgoIC9ezZU8uWLfP6OQIAAAAAAAAAAACe5tOiX/fu3bVv375q+7z++utVtg0cOFADBw6ssn3ChAmaMGHCeccHAAAAAAAAAPAcm61EmZlHqmzPzDwiu93uxYgAIHD5tOgHAAAAAAAAAKifrAUWHTp0UPMfXyhTQ1OlfQqLTutEVrZsthIvRwcAgee8in42m03bt2/Xrl27ZDabNXPmTMXGxuqHH35Qx44d6zpGAACAgEf+BAAA4D3kXkBgKCoukNEQqmt7jFbr+HaV9vnhwC6lHn1W9tJSL0cHAIHH7aLf8ePHNXr0aO3fv19RUVGyWq2aMmWKcnNz9Yc//EGrVq1S9+7dPRErAABAQCJ/AgAA8B5yL8DzzGazrNa8KtvdXZIzNjpe8c0SK23LzjnqdnwAUF+5XfSbP3++QkJCtGnTJnXu3FndunWTJF100UX605/+pGeeeUarV6+u80ABAAACFfkTAACA95B7AZ5lNps1eeJEFeQXVdmHJTkBwDfcLvp99tlneu6559S5c+dz2oYOHaoRI0bUSWAAAMB9Nb0AXZIiI5soLi7OSxFBIn8CAADwJnIvwLOs1jwV5BdpQI+7FBfTqtI+LMkJAL7hdtGvsLBQsbGxlbYZDAaVlHD3BoDg8uGDbynMekI/ZnynF7a9qD/+wdcRAZVz5QXokhQeEabFS5dS+PMi8icACCyDYhJ0z61zldCmg3fGW5yge0bMVUJL74wHBDtyL8A74mJasSRnPfLhg2/J4HDIaTS6vk/eW/r+56+0dvNC5tMAL3G76Ne+fXulpqZq2rRp57S9++67at++fZ0EBgD+oiiqhYrUQlkNrDqR5/aPTcBrXHkBujn3mLbtXCmrNY+inxeRPwFAYDkR0kD5TZqpKKqFd8bLa6B8WzMVOb0zHhDsyL0AoO6dT15U5Gwha0lT5tNQrrIVqgwG6dSpCOXk5MvpPLONVarOn9t/28aMGaMpU6bou+++0+WXX67S0lK98cYbOnTokLZv365FixZ5Ik4AAOCi6l6ADt8gfwIAAPAeci8AAPxPdStUNWgQIrv9f8sBs0rV+XO76Ddo0CA5HA698MILeuGFFyRJL774oi6++GItWLBA119/fZ0HCQAAEMjInwCgdsxms6zWvCrbMzOPyG63ezEiAP6M3AsAAP9T3QpVoaEhstnOFP1Ypap2zuu52htuuEE33HCD8vPzVVBQoMjISDVu3LiuYwMAv3DBv19T81afqqNOqqD3KV+HAyBAkT8BwPkxm82aPHGiCvKLquxTWHRaJ7KyZbPVzXu6bi88pd98tVFNDrXTwStuq5NjVjte71P6TdxGNTG108ESz48H1AfkXgBQty7492tqUFwge8Nwl/OjC0yvKTw+nfk0VFDZClUmUwOVlHATX11wq+hns9k0fPhwvfDCC2revLkiIiIUERHhqdgAwC903rpUjeZkqU2sNLlTiF477OuIAAQS8icAqB2rNU8F+UUa0OMuxcW0qrTPDwd2KfXos7KXllba7q7JBTlq+eEKFUbHe6XoN3lgjlpGr1ChI56iH1BL5F4A4Bmdty5VI0uWW/lR50ZLddkFWUqJZj4N8Ba3in6hoaHKy8vToUOH1Lx5c0/FBAAAEDTInwCgbsTFtKrynbXZOUe9HA0Af0XuBQAA6jO3l/d89NFH9cwzz+i6665TUlKSIiMjz+nTrl27SvYEAACon8ifAAAAvIfcCwAA1FduF/3GjBkjSfrqq69kMBgq7bN3797aRQUAABBEyJ8AAAC8h9wLAADUV24X/ebNm+eJOAAAAIIW+RMAAID3kHsBAID6yu2i38033+yJOAAAAIIW+RMAAID3kHsBAID6yu2inySlpaVpy5Yt2r9/vwoLCxUeHq6LL75YN910kzp06FDXMQIAAAQ88icAAADvIfcCAAD1kdHdHTZt2qRhw4bpjTfeUE5OjiTpl19+0dq1a3XzzTfr3XffrfMgAQAAAhn5EwAAgPeQewEAgPrK7Sf9nn32Wd1www2aO3euGjZsWL49Pz9fjz76qBYvXqzrr7++ToMEAAAIZORPAAAA3kPuBQAA6iu3n/Q7ceKE7rnnngpJkyRFRERo3LhxysrKqrPgAMAfWJu3k/1kI5Ucb6ifs02+DgdAACJ/AoDA8nOISeambWVt3s4742WbZC5qK2upd8YDgp0nc68nnnhCHTt2LP+8Y8cODR48WMnJyRowYIDeeuutCv1Xr16tfv36KSUlRcOGDVN6enp5W3FxsWbNmqXLL79c3bp103333Vf+ZCIA+Btr83bKi7/YrfzIWtpOJ063Zj4N8CK3n/Rr166dLBZLpW15eXlKTEysbUwA4Ff+fd86SdKefZ9rxfpHNOVOHwcEIOCQPwFAYLk1prWm3Pmc2iV08s54f/fueHCdzVaizMwj1faJjGyiuLg4L0UEV3gq99q7d682b95c/vn48eMaN26cpkyZomHDhmnHjh2aNGmSLrjgAqWkpGjbtm1asmSJnn/+eV1yySVauXKlxo4dq/fee0+NGzfWggULtGvXLm3cuFHh4eGaPn26HnroIb3wwgvnFR8AeFLZ/Jhb++SvYz4N8DK3i37Tp0/X008/rYcfflhdunQp375v3z4tXrxY06dPr9MAAQAAAh35EwBUzWw2y2rNq7I9M/OI7Ha7FyMCzrAWWHTo0EHNf3yhTA2rfkIhPCJMi5cupfDnRzyRezkcDj366KO64447tGTJEknSli1blJiYqFGjRkmS+vfvr2uuuUYbNmxQSkqKUlNTNXToUPXq1UuSNH78eK1bt04ffPCBrrvuOm3atEnz589XQkKCJGnatGkaNGiQjh8/rhYtWtTyqwAAAOojl4p+/fv3l8FgKP+cl5enP/zhD2rYsKGioqKUl5enoqIiRURE6Mknn9SWLVs8FjAAAEAgIH8CgJqZzWZNnjhRBflFVfYpLDqtE1nZstlKvBgZIBUVF8hoCNW1PUardXzlS5mZc49p286VslrzKPr5mKdzr3Xr1iksLEw33nhjedEvIyNDXbt2rdCvS5cuevfdd8vbBw0aVN5mMBjUuXNnpaWlqUuXLsrPz6+wf/v27dWoUSOlp6dT9AMAAOfFpaLf5ZdfXiFxqorT6ZTNZqt1UAAAAIGO/AkAama15qkgv0gDetyluJhWlfb54cAupR59VvbSUi9HB5wRGx2v+GYsxe3vPJl7mc1mPffcc1q7dm2F7bm5uerUqeKyvNHR0eXv5cvNzVV0dHSF9qioKOXk5Cg3N7f889maNGnCe/0AAMB5c6no9+STT3o6DgDwW91X3adm136uAXE2Jf/RrgO+DghAQCB/AgDXxcW0qrKokp1z1MvRSM+cytJl6x+SMa6Nvr5jmefH+2OWLmv3kIymNvr6tOfHA4KRJ3OvefPm6dZbb9WFF16ozMzM8u1VFRnLtlfXXl2Bsqq20NAQuVDXdFvZMU2mEDmddX981J6/XSOTKURGg0EGo2QwVvF9bjwTt8FgqLKPq/28fazzGU+SjEaDfn15guX8DEaDur9yn0z5OSqJiNXXdy5z6VjdG92nSzr/rJQ/ZumAD78XynqefY2C6doE+ni/vj4Go2Q0GGQyhchkCqkyLlTO7Xf6lcnPz5fVapWzkt80rVpVfocmAASiZj99qUZ/zpZipd6WEB047OuIAAQq8icACAy9bYVqefAbFVq8U3Ds3b5QLSO/UaHD+wVOIJjVRe61Y8cOpaWl6YknnjinLSYmRhaLpcK23NxcxcbGVtveoUOH8j4Wi0WNGzeWdOYpRIvFoqZNm1Yai83mmSeeywpKJSWlflFQwrn87RqVlJTK4XTK6ZCcjsoDcjokp/PM93VVfVzt5+1jnc94kuSopG+wnJ/T4VTcj1+okSVLhdHx5fvVdKy4Bl+oUVSWGrcP0c+Hffe9UNbz7GsUTNcm0Mf79fVxOiSH06mSklKVlLDah7vcLvp9/fXXeuihh3TkyJEq++zdu7dWQQEAAAQT8icAAADvqcvc66233lJWVpb69u0r6X+T+z179tRdd92lf/3rXxX67969WykpKZKk5ORkpaWlaciQIZKk0tJSZWRkaOjQoUpISFB0dLTS09PLC5D79u2TzWZTUlKSW+cLAABQxu2i32OPPSaTyaQHHnhAMTExLq2XDgAAUJ+RPwEAAHhPXeZe06dP18SJE8s/Z2Vlafjw4dq8ebMcDoeWL1+uVatWafjw4fr444/1ySef6I033pAkjRgxQhMnTtS1116rlJQUPffccwoLC1P//v0VEhKiW2+9VUuWLFGnTp3UuHFjzZs3T7/73e8UFxdX668BUBmz2SyrNa/GfpGRTfg+BIAA5XbR7/Dhw1q/fv05LyoGAABA5cifAAAAvKcuc6+oqChFRUWVf7bb7ZKk+Ph4SdLy5cs1Z84cLVq0SK1atdKiRYvKx+3bt6+mTp2qGTNm6OTJk0pKStKKFSvUsGFDSdKECRNUUFCgW265RaWlperXr59mz55d65iBypjNZk2eOFEF+UU19g2PCNPipUsp/AFAAHK76HfhhReWJzhAmZruFMrMPML3DQCg3iJ/AgAA8B5P5l5t2rTRvn37yj93795dmzdvrrL/yJEjNXLkyErbTCaTZs2apVmzZtV5nMCvWa15Ksgv0oAedykupup3Wppzj2nbzpWyWvMo+gFAAHK76Pfwww9rwYIFmjx5sjp37lx+dxLqL1fuFCosOq0TWdmy2Uq8GBkAAP6B/AkAAMB7yL2AqsXFtFJ8s8Rq+9hsJcrMrPqdmNzcDwD+y+2iX+PGjZWTk1PlXUoGg0EZGRm1DgyBw5U7hX44sEupR5+VvbTUy9EBAOB75E8AAADeQ+4FnD9rgUWHDh3U/McXytTQVGkfbu4HAP/ldtFvxowZOnXqlG677TZFR0fX6mXICC7V3SmUnXPUy9EAAOA/yJ8AAAC8h9wLOH9FxQUyGkJ1bY/Rah3frtI+3NwPAP7L7aLfgQMH9I9//EMpKSmeiAcAACDokD8BAAB4D7kXUHux0fHc3A8AAcjo7g6JiYkKDQ31RCwA4JcO/HakTh7opiO7LtKrX0T5OhwAAcgX+dPf//53XXHFFerWrZvuuOMOHTly5p0cO3bs0ODBg5WcnKwBAwborbfeqrDf6tWr1a9fP6WkpGjYsGFKT08vbysuLtasWbN0+eWXq1u3brrvvvuUk5Pj1fMCAG94tVGUvu5+iw78tvKlAet8vC+i9HX2LTpQ7J3xgGDH3BUA1L0Dvx2pH/vd5VZ+dKB4pHb8Moj5NMCL3C76zZkzR0uXLtXu3btVXFzsiZgAwK98P2iSPr7wTb1cMkeL/y/W1+EACEDezp9ee+01ffDBB1q/fr0++ugjtWzZUq+88oqOHz+ucePGaejQofrqq680Y8YMzZw5U7t375Ykbdu2TUuWLNG8efP05Zdf6qqrrtLYsWN1+vRpSdKCBQu0a9cubdy4Ue+//76Kior00EMPefx8AMDbFofH6uNrxur7QZO8M97/xerjX8bq+yLvjAcEO+auAKDufT9okvb8YZZb+dH3RZP03qE/MZ8GeJHby3vee++9Kioq0vDhwytt52XIAAAAFXk7f1q5cqWefvpptW7dWpI0b948SdJLL72kxMREjRo1SpLUv39/XXPNNdqwYYNSUlKUmpqqoUOHqlevXpKk8ePHa926dfrggw903XXXadOmTZo/f74SEhIkSdOmTdOgQYN0/PhxtWjRos7iBwAAqA3mrgAAQH3ldtHvD3/4A0skAAAAuMGb+dPx48eVlZWlQ4cO6cEHH9SpU6fUu3dvPfroo8rIyFDXrl0r9O/SpYveffddSVJGRoYGDRpU3mYwGNS5c2elpaWpS5cuys/Pr7B/+/bt1ahRI6Wnp1P0AwAAfoO5KwAAUF+5XfSbPHmyJ+IAAAAIWt7Mn7KysmQwGLR9+3atX79eRUVFuu+++/TII4+ooKBAnTp1qtA/Ojq6/L18ubm5io6OrtAeFRWlnJwc5ebmln8+W5MmTap8r19oaIgMhjo6sbOUHdNkCpHTWffHh2dw3QKPN66ZyRQio8Egg1EyGCv/gWEwnonFYDDUqk9dHsvfx5Mko9Ggyi6bv8ceiOMZDQaZTCEymUKqHK86/Hyse8xdAQCA+srtop8kFRUV6b333tPevXtVUFCgyMhIpaSkqH///txJBSDoXD+zpxrNydItvaS/dArRa4d9HRGAQOSt/Mlms8lms+nBBx9UTEyMJOm+++7TmDFj9Nvf/rbSfQz/nW0s+29l7VW1VbefzVbqTuguKxuupKSUydEAwnULPN64ZiUlpXI4nXI6JKej8kGcDsnplJxOZ636uHOsndkH1PLJgSqMjte7c7/0/HizDqhl9EAVOuL17qnajydJDi99rbx9bfxxPIfTqZKSUpWUnN/vPX4+egZzVwBQt66f2VONLFlV5keV7hPVU7f0ymI+DfAit4t+R44c0Z///GcdO3ZMISEhioiIkNVqlcPh0EUXXaRVq1YpLi7OrWN++umnmjZtmnr27KnFixeXb//nP/+phx566Jxk7NVXX1VKSoocDoeWLl2qDRs2KD8/X926ddOcOXPK3zOTm5urv/3tb/r4448VEhKigQMH6pFHHlFYWJi7pw0AAHDePJE/VaXsSb2IiIjyba1bt5bT6ZTNZpPFYqnQPzc3V7GxZ16qHhMTU2l7hw4dyvtYLBY1btxY0plJUIvFoqZNm9ZJ7AAAAHXBm7kXAACAPzG6u8OCBQsUERGh9evXKy0tTV9++aXS0tK0Zs0a2e12LVy40K3jvfjii5o7d64SExMrbe/Ro4f27NlT4U9KSookac2aNdq4caNWrlypzz77TAkJCRo/fryc/7017qGHHtLJkyf13nvv6V//+pf27t3rdnwAAAC1Vdf5U3USExMVERGh9PT08m1Hjx5VgwYNdPXVV1fYLkm7d+8uz62Sk5OVlpZW3lZaWqqMjAylpKQoISFB0dHRFfbft2+fbDabkpKS6ix+AACA2vJm7gUAAOBP3C76ffnll3rkkUd0ySWXlC/lZDQadfnll2vWrFn65JNP3Dpew4YNtWHDhiqLftVJTU3V3XffrU6dOikiIkLTpk3Tzz//rG+//VZms1kffvihZsyYobi4OLVo0UKTJk3Sxo0bVVJS4vZYAAAA56uu86fqhIaGatiwYVq4cKGysrKUnZ2t5557TjfddJOGDBmio0ePatWqVSosLNTWrVv1ySefaPjw4ZKkESNGaOPGjfriiy90+vRpPf300woLC1P//v0VEhKiW2+9VUuWLNGRI0d08uRJzZs3T7/73e+4Ux5Apcxmsw4c+LnaP5mZR2S3230dKoAg483cCwAA1D2brUSZmUeq/beE2Wz2dZh+ye3lPQsKCtS8efNK21q3bq28vDy3jjdq1Khq23/55Rf9+c9/Vnp6upo3b66xY8fqpptuUnFxsfbv31/hzvKIiAi1bdtWaWlpys/PV4MGDdSxY8fy9q5du+r06dM6cOBAhe0AAACeVNf5U02mTJmiJ598UoMHD5bRaFT//v310EMPKSIiQsuXL9ecOXO0aNEitWrVSosWLVKnTp0kSX379tXUqVM1Y8YMnTx5UklJSVqxYoUaNmwoSZowYYIKCgp0yy23qLS0VP369dPs2bPrNHYAwcFsNmvyxIkqyC+qtl9h0WmdyMqWzcaNmQDqjrdzLwAAUHesBRYdOnRQ8x9fKFNDU5X9wiPCtHjpUm5E/hW3i35t2rTRxx9/XGmx7qOPPlLr1q3rJDBJio2N1QUXXKCJEyfq4osv1vbt2zV16lQ1b95cF154oZxOp6KioirsExUVpZycHEVFRSkiIkJGo7FCmyTl5ORUOl5oaEj5C7TdVbafyRRS7168bTKFyGgwyGCUDMbKv4AG45mvkcFgqLKPq/2q61P2yWg01PpY3o492MYzGsvupjTI6eZxfB17dceSAu/alG3xt69nIH8vnO94Z/+MclbRxxvnZzQYZDKFyGQKqfJYwcwXv7O9mT9Jkslk0qxZszRr1qxz2rp3767NmzdXue/IkSM1cuRIt48LAGezWvNUkF+kAT3uUlxMqyr7/XBgl1KPPit7aakXowMQ7LydewEAgLpTVFwgoyFU1/YYrdbx7SrtY849pm07V8pqzaPo9ytuF/2GDh2qp556Sj/88IO6d++u6OhoWSwWffnll9qyZYseeOCBOgvu6quv1tVXX13++YYbbtC2bdu0YcMGTZ06tcr9DAZD+fINVbVXxmY7/39olh2ypKS03hX9SkpK5XA65XRITkflJ+90SE6n5HQ6q+zjar/q+pR9cjictT6Wt2MPtvEc/+3j+PU18vL51fWxpMC7NmVb/O3rGcjfC+c73tk/o3x5fg6nUyUlpSopqZ8TrL74ne3N/AkA/ElcTCvFN6v6VQ7ZOUe9GA2A+oLcCwCAwBcbHV/tvyVQObeLfnfffbcKCgq0Zs0abdiwoXx7ZGSkxo8frzvuuKMu4ztHmzZtlJaWppiYGBmNRlkslgrtubm5atq0qWJjY2W1WlVaWqqQkJDyNklq2rSpR2MEAAA4m6/zJwAAgPqE3AsAANRXbhf9JGnixIn661//qp9//ln5+fmKjIzUhRdeqAYNzutwVVq3bp1iYmL0u9/9rnzbgQMHlJCQIJPJpA4dOig9PV09evSQJFksFh0+fFjJyclKSEiQw+HQvn371KVLF0nS7t27FRkZqQsuuKBO4wQAAKiJt/InAJUzm82yWqt/h1NkZBOWhgGAIEHuBQAA6qPzznRCQ0PVsWPHuozlHHa7XXPmzFHbtm110UUX6f/+7//0ySefaP369ZLOvHPm2WefVa9evdS6dWvNnTtXSUlJSklJkSRdf/31mjdvnhYvXqzi4mItXrxYw4cPV2hoqEfjBgAAqIw38icA5zKbzZo8caIK8ouq7ceL4AEguJB7AQCA+salot+MGTN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      "text/plain": [
       "<Figure size 1800x500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Distribution des variables EXT_SOURCE\n",
    "fig, axes = plt.subplots(1, 3, figsize=(18, 5))\n",
    "\n",
    "for idx, col in enumerate(ext_source_cols):\n",
    "    axes[idx].hist(app_train[col].dropna(), bins=50, edgecolor='black', alpha=0.7, color='mediumpurple')\n",
    "    axes[idx].set_xlabel(col, fontsize=12)\n",
    "    axes[idx].set_ylabel('Nombre de clients', fontsize=12)\n",
    "    axes[idx].set_title(f'Distribution de {col}', fontsize=13, fontweight='bold')\n",
    "    axes[idx].grid(axis='y', alpha=0.3)\n",
    "    \n",
    "    # Statistiques\n",
    "    mean_val = app_train[col].mean()\n",
    "    median_val = app_train[col].median()\n",
    "    axes[idx].axvline(mean_val, color='red', linestyle='--', linewidth=2, label=f'Moyenne: {mean_val:.3f}')\n",
    "    axes[idx].axvline(median_val, color='orange', linestyle='--', linewidth=2, label=f'Médiane: {median_val:.3f}')\n",
    "    axes[idx].legend()\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "a286e6f2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1600x1200 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "💡 Observation clé : Les clients avec TARGET=1 ont des scores EXT_SOURCE plus faibles\n",
      "    → Ces variables sont des prédicteurs très importants du risque de défaut\n"
     ]
    }
   ],
   "source": [
    "# Comparaison des distributions EXT_SOURCE par TARGET\n",
    "fig, axes = plt.subplots(3, 2, figsize=(16, 12))\n",
    "\n",
    "for idx, col in enumerate(ext_source_cols):\n",
    "    # KDE Plot\n",
    "    sns.kdeplot(data=app_train[app_train['TARGET'] == 0][col].dropna(), \n",
    "                ax=axes[idx, 0], label='Pas de difficulté (TARGET=0)', \n",
    "                shade=True, color='#2ecc71')\n",
    "    sns.kdeplot(data=app_train[app_train['TARGET'] == 1][col].dropna(), \n",
    "                ax=axes[idx, 0], label='Difficulté (TARGET=1)', \n",
    "                shade=True, color='#e74c3c')\n",
    "    axes[idx, 0].set_xlabel(col, fontsize=11)\n",
    "    axes[idx, 0].set_ylabel('Densité', fontsize=11)\n",
    "    axes[idx, 0].set_title(f'Distribution de {col} par TARGET', fontsize=12, fontweight='bold')\n",
    "    axes[idx, 0].legend()\n",
    "    axes[idx, 0].grid(alpha=0.3)\n",
    "    \n",
    "    # Box Plot\n",
    "    data_to_plot = [\n",
    "        app_train[app_train['TARGET'] == 0][col].dropna(),\n",
    "        app_train[app_train['TARGET'] == 1][col].dropna()\n",
    "    ]\n",
    "    axes[idx, 1].boxplot(data_to_plot, labels=['TARGET=0', 'TARGET=1'], patch_artist=True,\n",
    "                         boxprops=dict(facecolor='lightblue'))\n",
    "    axes[idx, 1].set_ylabel(col, fontsize=11)\n",
    "    axes[idx, 1].set_title(f'Box Plot de {col} par TARGET', fontsize=12, fontweight='bold')\n",
    "    axes[idx, 1].grid(axis='y', alpha=0.3)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "print(\"\\n💡 Observation clé : Les clients avec TARGET=1 ont des scores EXT_SOURCE plus faibles\")\n",
    "print(\"    → Ces variables sont des prédicteurs très importants du risque de défaut\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "3ec0b214",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "📊 Insights :\n",
      "  • EXT_SOURCE_2 et EXT_SOURCE_3 ont les corrélations négatives les plus fortes avec TARGET\n",
      "  • Les trois variables EXT_SOURCE sont faiblement corrélées entre elles\n",
      "  → Elles apportent des informations complémentaires (peu de redondance)\n"
     ]
    }
   ],
   "source": [
    "# Matrice de corrélation des EXT_SOURCE avec TARGET\n",
    "ext_source_corr = app_train[ext_source_cols + ['TARGET']].corr()\n",
    "\n",
    "plt.figure(figsize=(10, 8))\n",
    "sns.heatmap(ext_source_corr, annot=True, fmt='.3f', cmap='RdYlBu_r', \n",
    "            center=0, square=True, linewidths=1, cbar_kws={\"shrink\": 0.8})\n",
    "plt.title('Matrice de Corrélation - Variables EXT_SOURCE et TARGET', \n",
    "          fontsize=14, fontweight='bold', pad=20)\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "print(\"\\n📊 Insights :\")\n",
    "print(\"  • EXT_SOURCE_2 et EXT_SOURCE_3 ont les corrélations négatives les plus fortes avec TARGET\")\n",
    "print(\"  • Les trois variables EXT_SOURCE sont faiblement corrélées entre elles\")\n",
    "print(\"  → Elles apportent des informations complémentaires (peu de redondance)\")"
   ]
  },
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   "cell_type": "markdown",
   "id": "8b79b970",
   "metadata": {},
   "source": [
    "## 11. Résumé et Conclusions\n",
    "\n",
    "### 📌 Découvertes Principales\n",
    "\n",
    "1. **Déséquilibre des Classes**\n",
    "   - 92% de clients sans difficulté vs 8% avec difficulté\n",
    "   - Nécessite des techniques de gestion du déséquilibre (pondération, SMOTE, etc.)\n",
    "\n",
    "2. **Valeurs Manquantes**\n",
    "   - Beaucoup de colonnes ont > 40% de valeurs manquantes\n",
    "   - Stratégies d'imputation ou sélection de features nécessaires\n",
    "\n",
    "3. **Variables Importantes Identifiées**\n",
    "   - **EXT_SOURCE_1, 2, 3** : Corrélations négatives fortes (prédicteurs clés)\n",
    "   - **DAYS_BIRTH (âge)** : Légère influence\n",
    "   - **DAYS_EMPLOYED** : Contient une anomalie (365243) à traiter\n",
    "\n",
    "4. **Anomalies Détectées**\n",
    "   - DAYS_EMPLOYED = 365243 (flag spécial créé)\n",
    "   - Valeurs remplacées par NaN pour éviter de biaiser les modèles\n",
    "\n",
    "5. **Patterns Observés**\n",
    "   - Les clients plus jeunes ont un risque légèrement plus élevé\n",
    "   - Les scores EXT_SOURCE bas sont fortement associés au défaut\n",
    "   - Les trois EXT_SOURCE sont peu corrélés → informations complémentaires\n",
    "\n",
    "### 🎯 Prochaines Étapes\n",
    "\n",
    "1. **Feature Engineering** (Notebook 02)\n",
    "   - Créer des interactions entre variables (polynomiales, ratios)\n",
    "   - Agréger les données des tables secondaires (bureau, previous_application, etc.)\n",
    "   - Créer des features temporelles\n",
    "\n",
    "2. **Preprocessing**\n",
    "   - Imputation des valeurs manquantes\n",
    "   - Encodage des variables catégorielles\n",
    "   - Normalisation/Standardisation\n",
    "\n",
    "3. **Modeling**\n",
    "   - Tester différents algorithmes (LightGBM, XGBoost, etc.)\n",
    "   - Gérer le déséquilibre des classes\n",
    "   - Optimisation des hyperparamètres\n",
    "   - Validation croisée stratifiée\n",
    "\n",
    "### 📚 Références\n",
    "- [Will Koehrsen - Start Here: A Gentle Introduction](https://www.kaggle.com/code/willkoehrsen/start-here-a-gentle-introduction)\n",
    "- [Home Credit Default Risk Competition](https://www.kaggle.com/c/home-credit-default-risk)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "f98593ad",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "💾 Préparation des données pour le notebook suivant...\n",
      "\n",
      "✓ Notebook d'exploration terminé\n",
      "✓ Passez au notebook 02_preparation_features.ipynb pour la suite\n"
     ]
    }
   ],
   "source": [
    "# Sauvegarde des données nettoyées pour le prochain notebook\n",
    "print(\"💾 Préparation des données pour le notebook suivant...\")\n",
    "\n",
    "# Note : Nous sauvegarderons les données transformées après feature engineering complet\n",
    "print(\"\\n✓ Notebook d'exploration terminé\")\n",
    "print(\"✓ Passez au notebook 02_preparation_features.ipynb pour la suite\")"
   ]
  }
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